{
 "cells": [
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "# 使用xgboost模型，当前得分0.81944"
   ]
  },
  {
   "attachments": {
    "364c81df-8dea-46f7-b790-dc6067ec4e61.png": {
     "image/png": 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"
    }
   },
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "![image.png](attachment:364c81df-8dea-46f7-b790-dc6067ec4e61.png)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 1,
   "metadata": {},
   "outputs": [],
   "source": [
    "# 从sklearn 调入所需要的包\n",
    "# from sklearn import datasets\n",
    "from sklearn.model_selection import train_test_split #数据分隔出训练集和验证集\n",
    "import lightgbm as lgb\n",
    "import numpy as np\n",
    "import pandas as pd\n",
    "#导入精度和召回\n",
    "from sklearn.metrics import precision_score, recall_score\n",
    "import lightgbm as lgb"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 2,
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "<class 'pandas.core.frame.DataFrame'>\n",
      "RangeIndex: 1176 entries, 0 to 1175\n",
      "Data columns (total 36 columns):\n",
      " #   Column                    Non-Null Count  Dtype \n",
      "---  ------                    --------------  ----- \n",
      " 0   user_id                   1176 non-null   int64 \n",
      " 1   Age                       1176 non-null   int64 \n",
      " 2   Attrition                 1176 non-null   object\n",
      " 3   BusinessTravel            1176 non-null   object\n",
      " 4   DailyRate                 1176 non-null   int64 \n",
      " 5   Department                1176 non-null   object\n",
      " 6   DistanceFromHome          1176 non-null   int64 \n",
      " 7   Education                 1176 non-null   int64 \n",
      " 8   EducationField            1176 non-null   object\n",
      " 9   EmployeeCount             1176 non-null   int64 \n",
      " 10  EmployeeNumber            1176 non-null   int64 \n",
      " 11  EnvironmentSatisfaction   1176 non-null   int64 \n",
      " 12  Gender                    1176 non-null   object\n",
      " 13  HourlyRate                1176 non-null   int64 \n",
      " 14  JobInvolvement            1176 non-null   int64 \n",
      " 15  JobLevel                  1176 non-null   int64 \n",
      " 16  JobRole                   1176 non-null   object\n",
      " 17  JobSatisfaction           1176 non-null   int64 \n",
      " 18  MaritalStatus             1176 non-null   object\n",
      " 19  MonthlyIncome             1176 non-null   int64 \n",
      " 20  MonthlyRate               1176 non-null   int64 \n",
      " 21  NumCompaniesWorked        1176 non-null   int64 \n",
      " 22  Over18                    1176 non-null   object\n",
      " 23  OverTime                  1176 non-null   object\n",
      " 24  PercentSalaryHike         1176 non-null   int64 \n",
      " 25  PerformanceRating         1176 non-null   int64 \n",
      " 26  RelationshipSatisfaction  1176 non-null   int64 \n",
      " 27  StandardHours             1176 non-null   int64 \n",
      " 28  StockOptionLevel          1176 non-null   int64 \n",
      " 29  TotalWorkingYears         1176 non-null   int64 \n",
      " 30  TrainingTimesLastYear     1176 non-null   int64 \n",
      " 31  WorkLifeBalance           1176 non-null   int64 \n",
      " 32  YearsAtCompany            1176 non-null   int64 \n",
      " 33  YearsInCurrentRole        1176 non-null   int64 \n",
      " 34  YearsSinceLastPromotion   1176 non-null   int64 \n",
      " 35  YearsWithCurrManager      1176 non-null   int64 \n",
      "dtypes: int64(27), object(9)\n",
      "memory usage: 330.9+ KB\n",
      "None\n",
      "<class 'pandas.core.frame.DataFrame'>\n",
      "RangeIndex: 294 entries, 0 to 293\n",
      "Data columns (total 35 columns):\n",
      " #   Column                    Non-Null Count  Dtype \n",
      "---  ------                    --------------  ----- \n",
      " 0   user_id                   294 non-null    int64 \n",
      " 1   Age                       294 non-null    int64 \n",
      " 2   BusinessTravel            294 non-null    object\n",
      " 3   DailyRate                 294 non-null    int64 \n",
      " 4   Department                294 non-null    object\n",
      " 5   DistanceFromHome          294 non-null    int64 \n",
      " 6   Education                 294 non-null    int64 \n",
      " 7   EducationField            294 non-null    object\n",
      " 8   EmployeeCount             294 non-null    int64 \n",
      " 9   EmployeeNumber            294 non-null    int64 \n",
      " 10  EnvironmentSatisfaction   294 non-null    int64 \n",
      " 11  Gender                    294 non-null    object\n",
      " 12  HourlyRate                294 non-null    int64 \n",
      " 13  JobInvolvement            294 non-null    int64 \n",
      " 14  JobLevel                  294 non-null    int64 \n",
      " 15  JobRole                   294 non-null    object\n",
      " 16  JobSatisfaction           294 non-null    int64 \n",
      " 17  MaritalStatus             294 non-null    object\n",
      " 18  MonthlyIncome             294 non-null    int64 \n",
      " 19  MonthlyRate               294 non-null    int64 \n",
      " 20  NumCompaniesWorked        294 non-null    int64 \n",
      " 21  Over18                    294 non-null    object\n",
      " 22  OverTime                  294 non-null    object\n",
      " 23  PercentSalaryHike         294 non-null    int64 \n",
      " 24  PerformanceRating         294 non-null    int64 \n",
      " 25  RelationshipSatisfaction  294 non-null    int64 \n",
      " 26  StandardHours             294 non-null    int64 \n",
      " 27  StockOptionLevel          294 non-null    int64 \n",
      " 28  TotalWorkingYears         294 non-null    int64 \n",
      " 29  TrainingTimesLastYear     294 non-null    int64 \n",
      " 30  WorkLifeBalance           294 non-null    int64 \n",
      " 31  YearsAtCompany            294 non-null    int64 \n",
      " 32  YearsInCurrentRole        294 non-null    int64 \n",
      " 33  YearsSinceLastPromotion   294 non-null    int64 \n",
      " 34  YearsWithCurrManager      294 non-null    int64 \n",
      "dtypes: int64(27), object(8)\n",
      "memory usage: 80.5+ KB\n",
      "None\n"
     ]
    }
   ],
   "source": [
    "path='./'\n",
    "train = pd.read_csv(path+'input/train.csv')\n",
    "test = pd.read_csv(path+'input/test.csv')\n",
    "print(train.info())\n",
    "print(test.info())"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 25,
   "metadata": {},
   "outputs": [
    {
     "data": {
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       "      <th>Department</th>\n",
       "      <th>DistanceFromHome</th>\n",
       "      <th>Education</th>\n",
       "      <th>EducationField</th>\n",
       "      <th>EmployeeCount</th>\n",
       "      <th>...</th>\n",
       "      <th>RelationshipSatisfaction</th>\n",
       "      <th>StandardHours</th>\n",
       "      <th>StockOptionLevel</th>\n",
       "      <th>TotalWorkingYears</th>\n",
       "      <th>TrainingTimesLastYear</th>\n",
       "      <th>WorkLifeBalance</th>\n",
       "      <th>YearsAtCompany</th>\n",
       "      <th>YearsInCurrentRole</th>\n",
       "      <th>YearsSinceLastPromotion</th>\n",
       "      <th>YearsWithCurrManager</th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
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       "      <th>0</th>\n",
       "      <td>1374</td>\n",
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       "      <td>...</td>\n",
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       "      <td>Research &amp; Development</td>\n",
       "      <td>28</td>\n",
       "      <td>3</td>\n",
       "      <td>Technical Degree</td>\n",
       "      <td>1</td>\n",
       "      <td>...</td>\n",
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       "      <td>1</td>\n",
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       "      <td>0</td>\n",
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       "    </tr>\n",
       "    <tr>\n",
       "      <th>2</th>\n",
       "      <td>768</td>\n",
       "      <td>40</td>\n",
       "      <td>0</td>\n",
       "      <td>Travel_Rarely</td>\n",
       "      <td>300</td>\n",
       "      <td>Sales</td>\n",
       "      <td>26</td>\n",
       "      <td>3</td>\n",
       "      <td>Marketing</td>\n",
       "      <td>1</td>\n",
       "      <td>...</td>\n",
       "      <td>2</td>\n",
       "      <td>80</td>\n",
       "      <td>1</td>\n",
       "      <td>8</td>\n",
       "      <td>3</td>\n",
       "      <td>2</td>\n",
       "      <td>7</td>\n",
       "      <td>7</td>\n",
       "      <td>7</td>\n",
       "      <td>5</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>3</th>\n",
       "      <td>569</td>\n",
       "      <td>36</td>\n",
       "      <td>0</td>\n",
       "      <td>Non-Travel</td>\n",
       "      <td>1434</td>\n",
       "      <td>Sales</td>\n",
       "      <td>8</td>\n",
       "      <td>4</td>\n",
       "      <td>Life Sciences</td>\n",
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       "      <td>9</td>\n",
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       "      <td>911</td>\n",
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       "      <td>1</td>\n",
       "      <td>Travel_Frequently</td>\n",
       "      <td>599</td>\n",
       "      <td>Sales</td>\n",
       "      <td>24</td>\n",
       "      <td>1</td>\n",
       "      <td>Life Sciences</td>\n",
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       "      <td>1</td>\n",
       "      <td>0</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "<p>5 rows × 36 columns</p>\n",
       "</div>"
      ],
      "text/plain": [
       "   user_id  Age  Attrition     BusinessTravel  DailyRate  \\\n",
       "0     1374   58          0      Travel_Rarely        605   \n",
       "1     1092   45          0      Travel_Rarely        950   \n",
       "2      768   40          0      Travel_Rarely        300   \n",
       "3      569   36          0         Non-Travel       1434   \n",
       "4      911   25          1  Travel_Frequently        599   \n",
       "\n",
       "               Department  DistanceFromHome  Education    EducationField  \\\n",
       "0                   Sales                21          3     Life Sciences   \n",
       "1  Research & Development                28          3  Technical Degree   \n",
       "2                   Sales                26          3         Marketing   \n",
       "3                   Sales                 8          4     Life Sciences   \n",
       "4                   Sales                24          1     Life Sciences   \n",
       "\n",
       "   EmployeeCount  ...  RelationshipSatisfaction  StandardHours  \\\n",
       "0              1  ...                         3             80   \n",
       "1              1  ...                         4             80   \n",
       "2              1  ...                         2             80   \n",
       "3              1  ...                         2             80   \n",
       "4              1  ...                         4             80   \n",
       "\n",
       "  StockOptionLevel  TotalWorkingYears  TrainingTimesLastYear  WorkLifeBalance  \\\n",
       "0                1                 29                      2                2   \n",
       "1                1                  8                      3                3   \n",
       "2                1                  8                      3                2   \n",
       "3                0                 10                      1                3   \n",
       "4                0                  1                      4                3   \n",
       "\n",
       "  YearsAtCompany  YearsInCurrentRole YearsSinceLastPromotion  \\\n",
       "0              1                   0                       0   \n",
       "1              5                   4                       0   \n",
       "2              7                   7                       7   \n",
       "3             10                   7                       0   \n",
       "4              1                   0                       1   \n",
       "\n",
       "   YearsWithCurrManager  \n",
       "0                     0  \n",
       "1                     3  \n",
       "2                     5  \n",
       "3                     9  \n",
       "4                     0  \n",
       "\n",
       "[5 rows x 36 columns]"
      ]
     },
     "execution_count": 25,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "train.head()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 4,
   "metadata": {},
   "outputs": [
    {
     "data": {
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       "      <td>Life Sciences</td>\n",
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       "      <td>1</td>\n",
       "      <td>0</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "<p>5 rows × 36 columns</p>\n",
       "</div>"
      ],
      "text/plain": [
       "   user_id  Age Attrition     BusinessTravel  DailyRate  \\\n",
       "0     1374   58        No      Travel_Rarely        605   \n",
       "1     1092   45        No      Travel_Rarely        950   \n",
       "2      768   40        No      Travel_Rarely        300   \n",
       "3      569   36        No         Non-Travel       1434   \n",
       "4      911   25       Yes  Travel_Frequently        599   \n",
       "\n",
       "               Department  DistanceFromHome  Education    EducationField  \\\n",
       "0                   Sales                21          3     Life Sciences   \n",
       "1  Research & Development                28          3  Technical Degree   \n",
       "2                   Sales                26          3         Marketing   \n",
       "3                   Sales                 8          4     Life Sciences   \n",
       "4                   Sales                24          1     Life Sciences   \n",
       "\n",
       "   EmployeeCount  ...  RelationshipSatisfaction  StandardHours  \\\n",
       "0              1  ...                         3             80   \n",
       "1              1  ...                         4             80   \n",
       "2              1  ...                         2             80   \n",
       "3              1  ...                         2             80   \n",
       "4              1  ...                         4             80   \n",
       "\n",
       "  StockOptionLevel  TotalWorkingYears  TrainingTimesLastYear  WorkLifeBalance  \\\n",
       "0                1                 29                      2                2   \n",
       "1                1                  8                      3                3   \n",
       "2                1                  8                      3                2   \n",
       "3                0                 10                      1                3   \n",
       "4                0                  1                      4                3   \n",
       "\n",
       "  YearsAtCompany  YearsInCurrentRole YearsSinceLastPromotion  \\\n",
       "0              1                   0                       0   \n",
       "1              5                   4                       0   \n",
       "2              7                   7                       7   \n",
       "3             10                   7                       0   \n",
       "4              1                   0                       1   \n",
       "\n",
       "   YearsWithCurrManager  \n",
       "0                     0  \n",
       "1                     3  \n",
       "2                     5  \n",
       "3                     9  \n",
       "4                     0  \n",
       "\n",
       "[5 rows x 36 columns]"
      ]
     },
     "execution_count": 4,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "train.head()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 10,
   "metadata": {},
   "outputs": [
    {
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       "      <td>no</td>\n",
       "      <td>no</td>\n",
       "      <td>cellular</td>\n",
       "      <td>30</td>\n",
       "      <td>jun</td>\n",
       "      <td>598</td>\n",
       "      <td>4</td>\n",
       "      <td>105</td>\n",
       "      <td>5</td>\n",
       "      <td>failure</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>4</th>\n",
       "      <td>25322</td>\n",
       "      <td>41</td>\n",
       "      <td>housemaid</td>\n",
       "      <td>married</td>\n",
       "      <td>secondary</td>\n",
       "      <td>no</td>\n",
       "      <td>0</td>\n",
       "      <td>yes</td>\n",
       "      <td>yes</td>\n",
       "      <td>cellular</td>\n",
       "      <td>15</td>\n",
       "      <td>jul</td>\n",
       "      <td>368</td>\n",
       "      <td>4</td>\n",
       "      <td>-1</td>\n",
       "      <td>0</td>\n",
       "      <td>unknown</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "</div>"
      ],
      "text/plain": [
       "      ID  age         job  marital  education default  balance housing loan  \\\n",
       "0  25318   51   housemaid  married    unknown      no      174      no   no   \n",
       "1  25319   32  management  married   tertiary      no     6059     yes   no   \n",
       "2  25320   60     retired  married    primary      no        0      no   no   \n",
       "3  25321   32     student   single   tertiary      no       64      no   no   \n",
       "4  25322   41   housemaid  married  secondary      no        0     yes  yes   \n",
       "\n",
       "     contact  day month  duration  campaign  pdays  previous poutcome  \n",
       "0  telephone   29   jul       308         3     -1         0  unknown  \n",
       "1   cellular   20   nov       110         2     -1         0  unknown  \n",
       "2  telephone   30   jul       130         3     -1         0  unknown  \n",
       "3   cellular   30   jun       598         4    105         5  failure  \n",
       "4   cellular   15   jul       368         4     -1         0  unknown  "
      ]
     },
     "execution_count": 10,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "test.head()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 4,
   "metadata": {},
   "outputs": [
    {
     "data": {
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       "<table border=\"1\" class=\"dataframe\">\n",
       "  <thead>\n",
       "    <tr style=\"text-align: right;\">\n",
       "      <th></th>\n",
       "      <th>user_id</th>\n",
       "      <th>Age</th>\n",
       "      <th>DailyRate</th>\n",
       "      <th>DistanceFromHome</th>\n",
       "      <th>Education</th>\n",
       "      <th>EmployeeCount</th>\n",
       "      <th>EmployeeNumber</th>\n",
       "      <th>EnvironmentSatisfaction</th>\n",
       "      <th>HourlyRate</th>\n",
       "      <th>JobInvolvement</th>\n",
       "      <th>...</th>\n",
       "      <th>RelationshipSatisfaction</th>\n",
       "      <th>StandardHours</th>\n",
       "      <th>StockOptionLevel</th>\n",
       "      <th>TotalWorkingYears</th>\n",
       "      <th>TrainingTimesLastYear</th>\n",
       "      <th>WorkLifeBalance</th>\n",
       "      <th>YearsAtCompany</th>\n",
       "      <th>YearsInCurrentRole</th>\n",
       "      <th>YearsSinceLastPromotion</th>\n",
       "      <th>YearsWithCurrManager</th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th>count</th>\n",
       "      <td>1176.000000</td>\n",
       "      <td>1176.000000</td>\n",
       "      <td>1176.000000</td>\n",
       "      <td>1176.000000</td>\n",
       "      <td>1176.000000</td>\n",
       "      <td>1176.0</td>\n",
       "      <td>1176.000000</td>\n",
       "      <td>1176.000000</td>\n",
       "      <td>1176.000000</td>\n",
       "      <td>1176.000000</td>\n",
       "      <td>...</td>\n",
       "      <td>1176.000000</td>\n",
       "      <td>1176.0</td>\n",
       "      <td>1176.000000</td>\n",
       "      <td>1176.000000</td>\n",
       "      <td>1176.000000</td>\n",
       "      <td>1176.000000</td>\n",
       "      <td>1176.000000</td>\n",
       "      <td>1176.00000</td>\n",
       "      <td>1176.000000</td>\n",
       "      <td>1176.000000</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>mean</th>\n",
       "      <td>736.124150</td>\n",
       "      <td>36.805272</td>\n",
       "      <td>802.033163</td>\n",
       "      <td>9.159864</td>\n",
       "      <td>2.918367</td>\n",
       "      <td>1.0</td>\n",
       "      <td>1026.960034</td>\n",
       "      <td>2.750850</td>\n",
       "      <td>65.130102</td>\n",
       "      <td>2.724490</td>\n",
       "      <td>...</td>\n",
       "      <td>2.714286</td>\n",
       "      <td>80.0</td>\n",
       "      <td>0.805272</td>\n",
       "      <td>11.161565</td>\n",
       "      <td>2.767007</td>\n",
       "      <td>2.764456</td>\n",
       "      <td>6.982143</td>\n",
       "      <td>4.19898</td>\n",
       "      <td>2.160714</td>\n",
       "      <td>4.098639</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>std</th>\n",
       "      <td>419.336964</td>\n",
       "      <td>9.065549</td>\n",
       "      <td>405.946729</td>\n",
       "      <td>8.137224</td>\n",
       "      <td>1.009809</td>\n",
       "      <td>0.0</td>\n",
       "      <td>594.763609</td>\n",
       "      <td>1.096221</td>\n",
       "      <td>20.294326</td>\n",
       "      <td>0.715027</td>\n",
       "      <td>...</td>\n",
       "      <td>1.080583</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.865611</td>\n",
       "      <td>7.747576</td>\n",
       "      <td>1.250756</td>\n",
       "      <td>0.713251</td>\n",
       "      <td>6.094338</td>\n",
       "      <td>3.63124</td>\n",
       "      <td>3.208052</td>\n",
       "      <td>3.564190</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>min</th>\n",
       "      <td>0.000000</td>\n",
       "      <td>18.000000</td>\n",
       "      <td>104.000000</td>\n",
       "      <td>1.000000</td>\n",
       "      <td>1.000000</td>\n",
       "      <td>1.0</td>\n",
       "      <td>1.000000</td>\n",
       "      <td>1.000000</td>\n",
       "      <td>30.000000</td>\n",
       "      <td>1.000000</td>\n",
       "      <td>...</td>\n",
       "      <td>1.000000</td>\n",
       "      <td>80.0</td>\n",
       "      <td>0.000000</td>\n",
       "      <td>0.000000</td>\n",
       "      <td>0.000000</td>\n",
       "      <td>1.000000</td>\n",
       "      <td>0.000000</td>\n",
       "      <td>0.00000</td>\n",
       "      <td>0.000000</td>\n",
       "      <td>0.000000</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>25%</th>\n",
       "      <td>374.750000</td>\n",
       "      <td>30.000000</td>\n",
       "      <td>463.500000</td>\n",
       "      <td>2.000000</td>\n",
       "      <td>2.000000</td>\n",
       "      <td>1.0</td>\n",
       "      <td>498.750000</td>\n",
       "      <td>2.000000</td>\n",
       "      <td>48.000000</td>\n",
       "      <td>2.000000</td>\n",
       "      <td>...</td>\n",
       "      <td>2.000000</td>\n",
       "      <td>80.0</td>\n",
       "      <td>0.000000</td>\n",
       "      <td>6.000000</td>\n",
       "      <td>2.000000</td>\n",
       "      <td>2.000000</td>\n",
       "      <td>3.000000</td>\n",
       "      <td>2.00000</td>\n",
       "      <td>0.000000</td>\n",
       "      <td>2.000000</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>50%</th>\n",
       "      <td>742.500000</td>\n",
       "      <td>36.000000</td>\n",
       "      <td>805.500000</td>\n",
       "      <td>7.000000</td>\n",
       "      <td>3.000000</td>\n",
       "      <td>1.0</td>\n",
       "      <td>1031.000000</td>\n",
       "      <td>3.000000</td>\n",
       "      <td>65.000000</td>\n",
       "      <td>3.000000</td>\n",
       "      <td>...</td>\n",
       "      <td>3.000000</td>\n",
       "      <td>80.0</td>\n",
       "      <td>1.000000</td>\n",
       "      <td>10.000000</td>\n",
       "      <td>3.000000</td>\n",
       "      <td>3.000000</td>\n",
       "      <td>5.000000</td>\n",
       "      <td>3.00000</td>\n",
       "      <td>1.000000</td>\n",
       "      <td>3.000000</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>75%</th>\n",
       "      <td>1101.250000</td>\n",
       "      <td>42.250000</td>\n",
       "      <td>1162.000000</td>\n",
       "      <td>14.000000</td>\n",
       "      <td>4.000000</td>\n",
       "      <td>1.0</td>\n",
       "      <td>1555.250000</td>\n",
       "      <td>4.000000</td>\n",
       "      <td>82.250000</td>\n",
       "      <td>3.000000</td>\n",
       "      <td>...</td>\n",
       "      <td>4.000000</td>\n",
       "      <td>80.0</td>\n",
       "      <td>1.000000</td>\n",
       "      <td>15.000000</td>\n",
       "      <td>3.000000</td>\n",
       "      <td>3.000000</td>\n",
       "      <td>9.000000</td>\n",
       "      <td>7.00000</td>\n",
       "      <td>2.250000</td>\n",
       "      <td>7.000000</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>max</th>\n",
       "      <td>1469.000000</td>\n",
       "      <td>60.000000</td>\n",
       "      <td>1499.000000</td>\n",
       "      <td>29.000000</td>\n",
       "      <td>5.000000</td>\n",
       "      <td>1.0</td>\n",
       "      <td>2068.000000</td>\n",
       "      <td>4.000000</td>\n",
       "      <td>100.000000</td>\n",
       "      <td>4.000000</td>\n",
       "      <td>...</td>\n",
       "      <td>4.000000</td>\n",
       "      <td>80.0</td>\n",
       "      <td>3.000000</td>\n",
       "      <td>40.000000</td>\n",
       "      <td>6.000000</td>\n",
       "      <td>4.000000</td>\n",
       "      <td>40.000000</td>\n",
       "      <td>18.00000</td>\n",
       "      <td>15.000000</td>\n",
       "      <td>17.000000</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "<p>8 rows × 27 columns</p>\n",
       "</div>"
      ],
      "text/plain": [
       "           user_id          Age    DailyRate  DistanceFromHome    Education  \\\n",
       "count  1176.000000  1176.000000  1176.000000       1176.000000  1176.000000   \n",
       "mean    736.124150    36.805272   802.033163          9.159864     2.918367   \n",
       "std     419.336964     9.065549   405.946729          8.137224     1.009809   \n",
       "min       0.000000    18.000000   104.000000          1.000000     1.000000   \n",
       "25%     374.750000    30.000000   463.500000          2.000000     2.000000   \n",
       "50%     742.500000    36.000000   805.500000          7.000000     3.000000   \n",
       "75%    1101.250000    42.250000  1162.000000         14.000000     4.000000   \n",
       "max    1469.000000    60.000000  1499.000000         29.000000     5.000000   \n",
       "\n",
       "       EmployeeCount  EmployeeNumber  EnvironmentSatisfaction   HourlyRate  \\\n",
       "count         1176.0     1176.000000              1176.000000  1176.000000   \n",
       "mean             1.0     1026.960034                 2.750850    65.130102   \n",
       "std              0.0      594.763609                 1.096221    20.294326   \n",
       "min              1.0        1.000000                 1.000000    30.000000   \n",
       "25%              1.0      498.750000                 2.000000    48.000000   \n",
       "50%              1.0     1031.000000                 3.000000    65.000000   \n",
       "75%              1.0     1555.250000                 4.000000    82.250000   \n",
       "max              1.0     2068.000000                 4.000000   100.000000   \n",
       "\n",
       "       JobInvolvement  ...  RelationshipSatisfaction  StandardHours  \\\n",
       "count     1176.000000  ...               1176.000000         1176.0   \n",
       "mean         2.724490  ...                  2.714286           80.0   \n",
       "std          0.715027  ...                  1.080583            0.0   \n",
       "min          1.000000  ...                  1.000000           80.0   \n",
       "25%          2.000000  ...                  2.000000           80.0   \n",
       "50%          3.000000  ...                  3.000000           80.0   \n",
       "75%          3.000000  ...                  4.000000           80.0   \n",
       "max          4.000000  ...                  4.000000           80.0   \n",
       "\n",
       "       StockOptionLevel  TotalWorkingYears  TrainingTimesLastYear  \\\n",
       "count       1176.000000        1176.000000            1176.000000   \n",
       "mean           0.805272          11.161565               2.767007   \n",
       "std            0.865611           7.747576               1.250756   \n",
       "min            0.000000           0.000000               0.000000   \n",
       "25%            0.000000           6.000000               2.000000   \n",
       "50%            1.000000          10.000000               3.000000   \n",
       "75%            1.000000          15.000000               3.000000   \n",
       "max            3.000000          40.000000               6.000000   \n",
       "\n",
       "       WorkLifeBalance  YearsAtCompany  YearsInCurrentRole  \\\n",
       "count      1176.000000     1176.000000          1176.00000   \n",
       "mean          2.764456        6.982143             4.19898   \n",
       "std           0.713251        6.094338             3.63124   \n",
       "min           1.000000        0.000000             0.00000   \n",
       "25%           2.000000        3.000000             2.00000   \n",
       "50%           3.000000        5.000000             3.00000   \n",
       "75%           3.000000        9.000000             7.00000   \n",
       "max           4.000000       40.000000            18.00000   \n",
       "\n",
       "       YearsSinceLastPromotion  YearsWithCurrManager  \n",
       "count              1176.000000           1176.000000  \n",
       "mean                  2.160714              4.098639  \n",
       "std                   3.208052              3.564190  \n",
       "min                   0.000000              0.000000  \n",
       "25%                   0.000000              2.000000  \n",
       "50%                   1.000000              3.000000  \n",
       "75%                   2.250000              7.000000  \n",
       "max                  15.000000             17.000000  \n",
       "\n",
       "[8 rows x 27 columns]"
      ]
     },
     "execution_count": 4,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "train.describe()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 5,
   "metadata": {},
   "outputs": [
    {
     "data": {
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       "  <thead>\n",
       "    <tr style=\"text-align: right;\">\n",
       "      <th></th>\n",
       "      <th>ID</th>\n",
       "      <th>age</th>\n",
       "      <th>balance</th>\n",
       "      <th>day</th>\n",
       "      <th>duration</th>\n",
       "      <th>campaign</th>\n",
       "      <th>pdays</th>\n",
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       "  <tbody>\n",
       "    <tr>\n",
       "      <th>count</th>\n",
       "      <td>10852.000000</td>\n",
       "      <td>10852.000000</td>\n",
       "      <td>10852.000000</td>\n",
       "      <td>10852.000000</td>\n",
       "      <td>10852.000000</td>\n",
       "      <td>10852.000000</td>\n",
       "      <td>10852.000000</td>\n",
       "      <td>10852.000000</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>mean</th>\n",
       "      <td>30743.500000</td>\n",
       "      <td>41.040638</td>\n",
       "      <td>1393.157298</td>\n",
       "      <td>15.680151</td>\n",
       "      <td>257.206137</td>\n",
       "      <td>2.770365</td>\n",
       "      <td>39.954755</td>\n",
       "      <td>0.546443</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>std</th>\n",
       "      <td>3132.846895</td>\n",
       "      <td>10.652369</td>\n",
       "      <td>3318.497101</td>\n",
       "      <td>8.302317</td>\n",
       "      <td>250.480906</td>\n",
       "      <td>3.063481</td>\n",
       "      <td>99.524056</td>\n",
       "      <td>1.805938</td>\n",
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       "    <tr>\n",
       "      <th>min</th>\n",
       "      <td>25318.000000</td>\n",
       "      <td>18.000000</td>\n",
       "      <td>-2604.000000</td>\n",
       "      <td>1.000000</td>\n",
       "      <td>0.000000</td>\n",
       "      <td>1.000000</td>\n",
       "      <td>-1.000000</td>\n",
       "      <td>0.000000</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>25%</th>\n",
       "      <td>28030.750000</td>\n",
       "      <td>33.000000</td>\n",
       "      <td>72.000000</td>\n",
       "      <td>8.000000</td>\n",
       "      <td>102.000000</td>\n",
       "      <td>1.000000</td>\n",
       "      <td>-1.000000</td>\n",
       "      <td>0.000000</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>50%</th>\n",
       "      <td>30743.500000</td>\n",
       "      <td>39.000000</td>\n",
       "      <td>450.000000</td>\n",
       "      <td>16.000000</td>\n",
       "      <td>181.000000</td>\n",
       "      <td>2.000000</td>\n",
       "      <td>-1.000000</td>\n",
       "      <td>0.000000</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>75%</th>\n",
       "      <td>33456.250000</td>\n",
       "      <td>49.000000</td>\n",
       "      <td>1440.250000</td>\n",
       "      <td>21.000000</td>\n",
       "      <td>322.000000</td>\n",
       "      <td>3.000000</td>\n",
       "      <td>-1.000000</td>\n",
       "      <td>0.000000</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>max</th>\n",
       "      <td>36169.000000</td>\n",
       "      <td>94.000000</td>\n",
       "      <td>81204.000000</td>\n",
       "      <td>31.000000</td>\n",
       "      <td>3102.000000</td>\n",
       "      <td>58.000000</td>\n",
       "      <td>871.000000</td>\n",
       "      <td>51.000000</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "</div>"
      ],
      "text/plain": [
       "                 ID           age       balance           day      duration  \\\n",
       "count  10852.000000  10852.000000  10852.000000  10852.000000  10852.000000   \n",
       "mean   30743.500000     41.040638   1393.157298     15.680151    257.206137   \n",
       "std     3132.846895     10.652369   3318.497101      8.302317    250.480906   \n",
       "min    25318.000000     18.000000  -2604.000000      1.000000      0.000000   \n",
       "25%    28030.750000     33.000000     72.000000      8.000000    102.000000   \n",
       "50%    30743.500000     39.000000    450.000000     16.000000    181.000000   \n",
       "75%    33456.250000     49.000000   1440.250000     21.000000    322.000000   \n",
       "max    36169.000000     94.000000  81204.000000     31.000000   3102.000000   \n",
       "\n",
       "           campaign         pdays      previous  \n",
       "count  10852.000000  10852.000000  10852.000000  \n",
       "mean       2.770365     39.954755      0.546443  \n",
       "std        3.063481     99.524056      1.805938  \n",
       "min        1.000000     -1.000000      0.000000  \n",
       "25%        1.000000     -1.000000      0.000000  \n",
       "50%        2.000000     -1.000000      0.000000  \n",
       "75%        3.000000     -1.000000      0.000000  \n",
       "max       58.000000    871.000000     51.000000  "
      ]
     },
     "execution_count": 5,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "test.describe()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 10,
   "metadata": {},
   "outputs": [
    {
     "data": {
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       "      <td>7</td>\n",
       "      <td>7</td>\n",
       "      <td>5</td>\n",
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       "      <th>3</th>\n",
       "      <td>569</td>\n",
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       "      <td>4</td>\n",
       "      <td>1</td>\n",
       "      <td>4</td>\n",
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       "    <tr>\n",
       "      <th>1173</th>\n",
       "      <td>1216</td>\n",
       "      <td>43</td>\n",
       "      <td>0</td>\n",
       "      <td>Travel_Rarely</td>\n",
       "      <td>1179</td>\n",
       "      <td>Sales</td>\n",
       "      <td>2</td>\n",
       "      <td>3</td>\n",
       "      <td>Medical</td>\n",
       "      <td>1</td>\n",
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       "      <td>684</td>\n",
       "      <td>40</td>\n",
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       "      <td>658</td>\n",
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       "      <td>11</td>\n",
       "      <td>2</td>\n",
       "      <td>2</td>\n",
       "      <td>1</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
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       "  </tbody>\n",
       "</table>\n",
       "<p>1176 rows × 36 columns</p>\n",
       "</div>"
      ],
      "text/plain": [
       "      user_id  Age  Attrition     BusinessTravel  DailyRate  \\\n",
       "0        1374   58          0      Travel_Rarely        605   \n",
       "1        1092   45          0      Travel_Rarely        950   \n",
       "2         768   40          0      Travel_Rarely        300   \n",
       "3         569   36          0         Non-Travel       1434   \n",
       "4         911   25          1  Travel_Frequently        599   \n",
       "...       ...  ...        ...                ...        ...   \n",
       "1171      763   34          0      Travel_Rarely       1333   \n",
       "1172      835   35          0      Travel_Rarely        528   \n",
       "1173     1216   43          0      Travel_Rarely       1179   \n",
       "1174      559   38          0      Travel_Rarely        268   \n",
       "1175      684   40          0      Travel_Rarely        658   \n",
       "\n",
       "                  Department  DistanceFromHome  Education    EducationField  \\\n",
       "0                      Sales                21          3     Life Sciences   \n",
       "1     Research & Development                28          3  Technical Degree   \n",
       "2                      Sales                26          3         Marketing   \n",
       "3                      Sales                 8          4     Life Sciences   \n",
       "4                      Sales                24          1     Life Sciences   \n",
       "...                      ...               ...        ...               ...   \n",
       "1171                   Sales                10          4     Life Sciences   \n",
       "1172         Human Resources                 8          4  Technical Degree   \n",
       "1173                   Sales                 2          3           Medical   \n",
       "1174  Research & Development                 2          5           Medical   \n",
       "1175                   Sales                10          4         Marketing   \n",
       "\n",
       "      EmployeeCount  ...  RelationshipSatisfaction  StandardHours  \\\n",
       "0                 1  ...                         3             80   \n",
       "1                 1  ...                         4             80   \n",
       "2                 1  ...                         2             80   \n",
       "3                 1  ...                         2             80   \n",
       "4                 1  ...                         4             80   \n",
       "...             ...  ...                       ...            ...   \n",
       "1171              1  ...                         4             80   \n",
       "1172              1  ...                         2             80   \n",
       "1173              1  ...                         1             80   \n",
       "1174              1  ...                         2             80   \n",
       "1175              1  ...                         2             80   \n",
       "\n",
       "     StockOptionLevel  TotalWorkingYears  TrainingTimesLastYear  \\\n",
       "0                   1                 29                      2   \n",
       "1                   1                  8                      3   \n",
       "2                   1                  8                      3   \n",
       "3                   0                 10                      1   \n",
       "4                   0                  1                      4   \n",
       "...               ...                ...                    ...   \n",
       "1171                1                  1                      2   \n",
       "1172                0                  6                      2   \n",
       "1173                1                 10                      3   \n",
       "1174                1                  6                      0   \n",
       "1175                1                 11                      2   \n",
       "\n",
       "      WorkLifeBalance YearsAtCompany  YearsInCurrentRole  \\\n",
       "0                   2              1                   0   \n",
       "1                   3              5                   4   \n",
       "2                   2              7                   7   \n",
       "3                   3             10                   7   \n",
       "4                   3              1                   0   \n",
       "...               ...            ...                 ...   \n",
       "1171                3              1                   1   \n",
       "1172                1              5                   4   \n",
       "1173                3             10                   9   \n",
       "1174                1              1                   0   \n",
       "1175                2              1                   0   \n",
       "\n",
       "     YearsSinceLastPromotion  YearsWithCurrManager  \n",
       "0                          0                     0  \n",
       "1                          0                     3  \n",
       "2                          7                     5  \n",
       "3                          0                     9  \n",
       "4                          1                     0  \n",
       "...                      ...                   ...  \n",
       "1171                       0                     0  \n",
       "1172                       1                     4  \n",
       "1173                       8                     8  \n",
       "1174                       0                     1  \n",
       "1175                       0                     0  \n",
       "\n",
       "[1176 rows x 36 columns]"
      ]
     },
     "execution_count": 10,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "train"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "metadata": {},
   "outputs": [],
   "source": [
    "'StandardHours',EmployeeCount"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 31,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "80    1470\n",
       "Name: StandardHours, dtype: int64"
      ]
     },
     "execution_count": 31,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "data['StandardHours'].value_counts()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 32,
   "metadata": {},
   "outputs": [
    {
     "data": {
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       "      <th>Age</th>\n",
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       "      <td>0.317604</td>\n",
       "      <td>0.220128</td>\n",
       "      <td>0.213677</td>\n",
       "      <td>0.204173</td>\n",
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       "    <tr>\n",
       "      <th>Attrition</th>\n",
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       "      <td>-0.073935</td>\n",
       "      <td>-0.141555</td>\n",
       "      <td>-0.169024</td>\n",
       "      <td>-0.042846</td>\n",
       "      <td>-0.163825</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>DailyRate</th>\n",
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       "      <td>0.016997</td>\n",
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       "      <td>1.000000</td>\n",
       "      <td>-0.013230</td>\n",
       "      <td>-0.013333</td>\n",
       "      <td>NaN</td>\n",
       "      <td>-0.040680</td>\n",
       "      <td>0.013415</td>\n",
       "      <td>0.024577</td>\n",
       "      <td>...</td>\n",
       "      <td>0.000101</td>\n",
       "      <td>NaN</td>\n",
       "      <td>0.045414</td>\n",
       "      <td>0.022416</td>\n",
       "      <td>0.000097</td>\n",
       "      <td>-0.017483</td>\n",
       "      <td>-0.021911</td>\n",
       "      <td>0.027265</td>\n",
       "      <td>-0.015516</td>\n",
       "      <td>-0.002437</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>DistanceFromHome</th>\n",
       "      <td>0.029618</td>\n",
       "      <td>-0.006119</td>\n",
       "      <td>0.072157</td>\n",
       "      <td>-0.013230</td>\n",
       "      <td>1.000000</td>\n",
       "      <td>-0.005039</td>\n",
       "      <td>NaN</td>\n",
       "      <td>0.029432</td>\n",
       "      <td>-0.013182</td>\n",
       "      <td>0.024524</td>\n",
       "      <td>...</td>\n",
       "      <td>0.028912</td>\n",
       "      <td>NaN</td>\n",
       "      <td>0.056862</td>\n",
       "      <td>-0.005337</td>\n",
       "      <td>-0.051527</td>\n",
       "      <td>-0.010663</td>\n",
       "      <td>-0.003907</td>\n",
       "      <td>0.015311</td>\n",
       "      <td>-0.005778</td>\n",
       "      <td>0.014304</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>Education</th>\n",
       "      <td>0.058138</td>\n",
       "      <td>0.201116</td>\n",
       "      <td>-0.033683</td>\n",
       "      <td>-0.013333</td>\n",
       "      <td>-0.005039</td>\n",
       "      <td>1.000000</td>\n",
       "      <td>NaN</td>\n",
       "      <td>0.058453</td>\n",
       "      <td>-0.038378</td>\n",
       "      <td>0.004381</td>\n",
       "      <td>...</td>\n",
       "      <td>0.000446</td>\n",
       "      <td>NaN</td>\n",
       "      <td>0.016850</td>\n",
       "      <td>0.148434</td>\n",
       "      <td>-0.016419</td>\n",
       "      <td>0.026454</td>\n",
       "      <td>0.070153</td>\n",
       "      <td>0.063850</td>\n",
       "      <td>0.043986</td>\n",
       "      <td>0.063246</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>EmployeeCount</th>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>...</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>EmployeeNumber</th>\n",
       "      <td>0.999906</td>\n",
       "      <td>0.009602</td>\n",
       "      <td>-0.009786</td>\n",
       "      <td>-0.040680</td>\n",
       "      <td>0.029432</td>\n",
       "      <td>0.058453</td>\n",
       "      <td>NaN</td>\n",
       "      <td>1.000000</td>\n",
       "      <td>0.042183</td>\n",
       "      <td>0.015261</td>\n",
       "      <td>...</td>\n",
       "      <td>-0.064441</td>\n",
       "      <td>NaN</td>\n",
       "      <td>0.041471</td>\n",
       "      <td>-0.009325</td>\n",
       "      <td>-0.018590</td>\n",
       "      <td>0.005984</td>\n",
       "      <td>-0.019196</td>\n",
       "      <td>-0.019196</td>\n",
       "      <td>-0.016330</td>\n",
       "      <td>-0.025114</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>EnvironmentSatisfaction</th>\n",
       "      <td>0.042355</td>\n",
       "      <td>0.016010</td>\n",
       "      <td>-0.095627</td>\n",
       "      <td>0.013415</td>\n",
       "      <td>-0.013182</td>\n",
       "      <td>-0.038378</td>\n",
       "      <td>NaN</td>\n",
       "      <td>0.042183</td>\n",
       "      <td>1.000000</td>\n",
       "      <td>-0.048388</td>\n",
       "      <td>...</td>\n",
       "      <td>0.018885</td>\n",
       "      <td>NaN</td>\n",
       "      <td>-0.002740</td>\n",
       "      <td>-0.004375</td>\n",
       "      <td>-0.014442</td>\n",
       "      <td>0.038081</td>\n",
       "      <td>-0.003979</td>\n",
       "      <td>0.028714</td>\n",
       "      <td>0.016720</td>\n",
       "      <td>-0.008952</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>HourlyRate</th>\n",
       "      <td>0.014785</td>\n",
       "      <td>0.035942</td>\n",
       "      <td>-0.003484</td>\n",
       "      <td>0.024577</td>\n",
       "      <td>0.024524</td>\n",
       "      <td>0.004381</td>\n",
       "      <td>NaN</td>\n",
       "      <td>0.015261</td>\n",
       "      <td>-0.048388</td>\n",
       "      <td>1.000000</td>\n",
       "      <td>...</td>\n",
       "      <td>0.008333</td>\n",
       "      <td>NaN</td>\n",
       "      <td>0.039087</td>\n",
       "      <td>0.000532</td>\n",
       "      <td>-0.023348</td>\n",
       "      <td>-0.012992</td>\n",
       "      <td>-0.011851</td>\n",
       "      <td>-0.011254</td>\n",
       "      <td>-0.001080</td>\n",
       "      <td>-0.021674</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>JobInvolvement</th>\n",
       "      <td>-0.012119</td>\n",
       "      <td>0.043840</td>\n",
       "      <td>-0.114287</td>\n",
       "      <td>0.045446</td>\n",
       "      <td>0.020156</td>\n",
       "      <td>0.052512</td>\n",
       "      <td>NaN</td>\n",
       "      <td>-0.011711</td>\n",
       "      <td>0.000299</td>\n",
       "      <td>0.070095</td>\n",
       "      <td>...</td>\n",
       "      <td>0.036821</td>\n",
       "      <td>NaN</td>\n",
       "      <td>0.001249</td>\n",
       "      <td>0.023866</td>\n",
       "      <td>-0.037580</td>\n",
       "      <td>-0.022222</td>\n",
       "      <td>0.004729</td>\n",
       "      <td>0.018510</td>\n",
       "      <td>-0.013330</td>\n",
       "      <td>0.036053</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>JobLevel</th>\n",
       "      <td>-0.009289</td>\n",
       "      <td>0.521973</td>\n",
       "      <td>-0.172917</td>\n",
       "      <td>0.004230</td>\n",
       "      <td>0.006961</td>\n",
       "      <td>0.106913</td>\n",
       "      <td>NaN</td>\n",
       "      <td>-0.009964</td>\n",
       "      <td>0.011368</td>\n",
       "      <td>-0.021629</td>\n",
       "      <td>...</td>\n",
       "      <td>0.008952</td>\n",
       "      <td>NaN</td>\n",
       "      <td>0.030808</td>\n",
       "      <td>0.785153</td>\n",
       "      <td>0.002550</td>\n",
       "      <td>0.039172</td>\n",
       "      <td>0.526776</td>\n",
       "      <td>0.381651</td>\n",
       "      <td>0.352960</td>\n",
       "      <td>0.368002</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>JobSatisfaction</th>\n",
       "      <td>-0.046578</td>\n",
       "      <td>0.003564</td>\n",
       "      <td>-0.098544</td>\n",
       "      <td>0.042196</td>\n",
       "      <td>0.003149</td>\n",
       "      <td>-0.002777</td>\n",
       "      <td>NaN</td>\n",
       "      <td>-0.046731</td>\n",
       "      <td>-0.016361</td>\n",
       "      <td>-0.065127</td>\n",
       "      <td>...</td>\n",
       "      <td>-0.023371</td>\n",
       "      <td>NaN</td>\n",
       "      <td>0.031976</td>\n",
       "      <td>-0.022147</td>\n",
       "      <td>-0.023552</td>\n",
       "      <td>-0.012945</td>\n",
       "      <td>-0.029844</td>\n",
       "      <td>-0.030511</td>\n",
       "      <td>-0.049939</td>\n",
       "      <td>-0.049388</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>MonthlyIncome</th>\n",
       "      <td>-0.004551</td>\n",
       "      <td>0.512036</td>\n",
       "      <td>-0.163906</td>\n",
       "      <td>0.010181</td>\n",
       "      <td>-0.018398</td>\n",
       "      <td>0.103431</td>\n",
       "      <td>NaN</td>\n",
       "      <td>-0.005157</td>\n",
       "      <td>0.004277</td>\n",
       "      <td>-0.014367</td>\n",
       "      <td>...</td>\n",
       "      <td>0.008674</td>\n",
       "      <td>NaN</td>\n",
       "      <td>0.022962</td>\n",
       "      <td>0.774175</td>\n",
       "      <td>0.000405</td>\n",
       "      <td>0.022595</td>\n",
       "      <td>0.511371</td>\n",
       "      <td>0.361812</td>\n",
       "      <td>0.353480</td>\n",
       "      <td>0.339039</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>MonthlyRate</th>\n",
       "      <td>0.008913</td>\n",
       "      <td>0.009248</td>\n",
       "      <td>0.034358</td>\n",
       "      <td>-0.019472</td>\n",
       "      <td>0.009890</td>\n",
       "      <td>-0.039819</td>\n",
       "      <td>NaN</td>\n",
       "      <td>0.009164</td>\n",
       "      <td>0.030246</td>\n",
       "      <td>-0.024027</td>\n",
       "      <td>...</td>\n",
       "      <td>-0.015298</td>\n",
       "      <td>NaN</td>\n",
       "      <td>-0.051149</td>\n",
       "      <td>0.021866</td>\n",
       "      <td>-0.004748</td>\n",
       "      <td>0.026192</td>\n",
       "      <td>-0.026878</td>\n",
       "      <td>-0.008505</td>\n",
       "      <td>-0.011861</td>\n",
       "      <td>-0.028764</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>NumCompaniesWorked</th>\n",
       "      <td>0.020461</td>\n",
       "      <td>0.321967</td>\n",
       "      <td>0.037556</td>\n",
       "      <td>0.020453</td>\n",
       "      <td>-0.044021</td>\n",
       "      <td>0.127862</td>\n",
       "      <td>NaN</td>\n",
       "      <td>0.019587</td>\n",
       "      <td>0.010484</td>\n",
       "      <td>0.015841</td>\n",
       "      <td>...</td>\n",
       "      <td>0.059753</td>\n",
       "      <td>NaN</td>\n",
       "      <td>0.024583</td>\n",
       "      <td>0.261906</td>\n",
       "      <td>-0.064855</td>\n",
       "      <td>-0.001043</td>\n",
       "      <td>-0.088854</td>\n",
       "      <td>-0.068468</td>\n",
       "      <td>-0.005041</td>\n",
       "      <td>-0.097412</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>PercentSalaryHike</th>\n",
       "      <td>-0.010746</td>\n",
       "      <td>0.020275</td>\n",
       "      <td>-0.041065</td>\n",
       "      <td>0.020790</td>\n",
       "      <td>0.024150</td>\n",
       "      <td>-0.025471</td>\n",
       "      <td>NaN</td>\n",
       "      <td>-0.010404</td>\n",
       "      <td>-0.017302</td>\n",
       "      <td>0.008183</td>\n",
       "      <td>...</td>\n",
       "      <td>-0.035117</td>\n",
       "      <td>NaN</td>\n",
       "      <td>0.026610</td>\n",
       "      <td>-0.007065</td>\n",
       "      <td>-0.010487</td>\n",
       "      <td>-0.008441</td>\n",
       "      <td>-0.014789</td>\n",
       "      <td>0.031146</td>\n",
       "      <td>-0.014727</td>\n",
       "      <td>0.002441</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>PerformanceRating</th>\n",
       "      <td>-0.020788</td>\n",
       "      <td>0.001435</td>\n",
       "      <td>-0.001920</td>\n",
       "      <td>-0.008661</td>\n",
       "      <td>0.020380</td>\n",
       "      <td>-0.043706</td>\n",
       "      <td>NaN</td>\n",
       "      <td>-0.020664</td>\n",
       "      <td>-0.014976</td>\n",
       "      <td>0.005624</td>\n",
       "      <td>...</td>\n",
       "      <td>-0.029566</td>\n",
       "      <td>NaN</td>\n",
       "      <td>0.015025</td>\n",
       "      <td>0.010257</td>\n",
       "      <td>-0.035685</td>\n",
       "      <td>-0.001030</td>\n",
       "      <td>0.014116</td>\n",
       "      <td>0.051615</td>\n",
       "      <td>0.015243</td>\n",
       "      <td>0.023724</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>RelationshipSatisfaction</th>\n",
       "      <td>-0.064190</td>\n",
       "      <td>0.059735</td>\n",
       "      <td>-0.034985</td>\n",
       "      <td>0.000101</td>\n",
       "      <td>0.028912</td>\n",
       "      <td>0.000446</td>\n",
       "      <td>NaN</td>\n",
       "      <td>-0.064441</td>\n",
       "      <td>0.018885</td>\n",
       "      <td>0.008333</td>\n",
       "      <td>...</td>\n",
       "      <td>1.000000</td>\n",
       "      <td>NaN</td>\n",
       "      <td>-0.026776</td>\n",
       "      <td>0.028391</td>\n",
       "      <td>0.015563</td>\n",
       "      <td>0.010885</td>\n",
       "      <td>0.017059</td>\n",
       "      <td>-0.023239</td>\n",
       "      <td>0.030197</td>\n",
       "      <td>-0.000852</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>StandardHours</th>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>...</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>StockOptionLevel</th>\n",
       "      <td>0.041794</td>\n",
       "      <td>0.045595</td>\n",
       "      <td>-0.129769</td>\n",
       "      <td>0.045414</td>\n",
       "      <td>0.056862</td>\n",
       "      <td>0.016850</td>\n",
       "      <td>NaN</td>\n",
       "      <td>0.041471</td>\n",
       "      <td>-0.002740</td>\n",
       "      <td>0.039087</td>\n",
       "      <td>...</td>\n",
       "      <td>-0.026776</td>\n",
       "      <td>NaN</td>\n",
       "      <td>1.000000</td>\n",
       "      <td>0.026650</td>\n",
       "      <td>-0.025434</td>\n",
       "      <td>0.015246</td>\n",
       "      <td>0.027250</td>\n",
       "      <td>0.056742</td>\n",
       "      <td>0.027216</td>\n",
       "      <td>0.037954</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>TotalWorkingYears</th>\n",
       "      <td>-0.008958</td>\n",
       "      <td>0.686609</td>\n",
       "      <td>-0.181079</td>\n",
       "      <td>0.022416</td>\n",
       "      <td>-0.005337</td>\n",
       "      <td>0.148434</td>\n",
       "      <td>NaN</td>\n",
       "      <td>-0.009325</td>\n",
       "      <td>-0.004375</td>\n",
       "      <td>0.000532</td>\n",
       "      <td>...</td>\n",
       "      <td>0.028391</td>\n",
       "      <td>NaN</td>\n",
       "      <td>0.026650</td>\n",
       "      <td>1.000000</td>\n",
       "      <td>-0.032999</td>\n",
       "      <td>0.001194</td>\n",
       "      <td>0.634263</td>\n",
       "      <td>0.462848</td>\n",
       "      <td>0.409752</td>\n",
       "      <td>0.461941</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>TrainingTimesLastYear</th>\n",
       "      <td>-0.018542</td>\n",
       "      <td>-0.014888</td>\n",
       "      <td>-0.056043</td>\n",
       "      <td>0.000097</td>\n",
       "      <td>-0.051527</td>\n",
       "      <td>-0.016419</td>\n",
       "      <td>NaN</td>\n",
       "      <td>-0.018590</td>\n",
       "      <td>-0.014442</td>\n",
       "      <td>-0.023348</td>\n",
       "      <td>...</td>\n",
       "      <td>0.015563</td>\n",
       "      <td>NaN</td>\n",
       "      <td>-0.025434</td>\n",
       "      <td>-0.032999</td>\n",
       "      <td>1.000000</td>\n",
       "      <td>0.019520</td>\n",
       "      <td>0.011289</td>\n",
       "      <td>-0.000465</td>\n",
       "      <td>0.016340</td>\n",
       "      <td>0.000387</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>WorkLifeBalance</th>\n",
       "      <td>0.006358</td>\n",
       "      <td>-0.018682</td>\n",
       "      <td>-0.073935</td>\n",
       "      <td>-0.017483</td>\n",
       "      <td>-0.010663</td>\n",
       "      <td>0.026454</td>\n",
       "      <td>NaN</td>\n",
       "      <td>0.005984</td>\n",
       "      <td>0.038081</td>\n",
       "      <td>-0.012992</td>\n",
       "      <td>...</td>\n",
       "      <td>0.010885</td>\n",
       "      <td>NaN</td>\n",
       "      <td>0.015246</td>\n",
       "      <td>0.001194</td>\n",
       "      <td>0.019520</td>\n",
       "      <td>1.000000</td>\n",
       "      <td>0.007255</td>\n",
       "      <td>0.055572</td>\n",
       "      <td>0.015814</td>\n",
       "      <td>0.002117</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>YearsAtCompany</th>\n",
       "      <td>-0.019605</td>\n",
       "      <td>0.317604</td>\n",
       "      <td>-0.141555</td>\n",
       "      <td>-0.021911</td>\n",
       "      <td>-0.003907</td>\n",
       "      <td>0.070153</td>\n",
       "      <td>NaN</td>\n",
       "      <td>-0.019196</td>\n",
       "      <td>-0.003979</td>\n",
       "      <td>-0.011851</td>\n",
       "      <td>...</td>\n",
       "      <td>0.017059</td>\n",
       "      <td>NaN</td>\n",
       "      <td>0.027250</td>\n",
       "      <td>0.634263</td>\n",
       "      <td>0.011289</td>\n",
       "      <td>0.007255</td>\n",
       "      <td>1.000000</td>\n",
       "      <td>0.752043</td>\n",
       "      <td>0.620109</td>\n",
       "      <td>0.775746</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>YearsInCurrentRole</th>\n",
       "      <td>-0.019685</td>\n",
       "      <td>0.220128</td>\n",
       "      <td>-0.169024</td>\n",
       "      <td>0.027265</td>\n",
       "      <td>0.015311</td>\n",
       "      <td>0.063850</td>\n",
       "      <td>NaN</td>\n",
       "      <td>-0.019196</td>\n",
       "      <td>0.028714</td>\n",
       "      <td>-0.011254</td>\n",
       "      <td>...</td>\n",
       "      <td>-0.023239</td>\n",
       "      <td>NaN</td>\n",
       "      <td>0.056742</td>\n",
       "      <td>0.462848</td>\n",
       "      <td>-0.000465</td>\n",
       "      <td>0.055572</td>\n",
       "      <td>0.752043</td>\n",
       "      <td>1.000000</td>\n",
       "      <td>0.547815</td>\n",
       "      <td>0.703930</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>YearsSinceLastPromotion</th>\n",
       "      <td>-0.016308</td>\n",
       "      <td>0.213677</td>\n",
       "      <td>-0.042846</td>\n",
       "      <td>-0.015516</td>\n",
       "      <td>-0.005778</td>\n",
       "      <td>0.043986</td>\n",
       "      <td>NaN</td>\n",
       "      <td>-0.016330</td>\n",
       "      <td>0.016720</td>\n",
       "      <td>-0.001080</td>\n",
       "      <td>...</td>\n",
       "      <td>0.030197</td>\n",
       "      <td>NaN</td>\n",
       "      <td>0.027216</td>\n",
       "      <td>0.409752</td>\n",
       "      <td>0.016340</td>\n",
       "      <td>0.015814</td>\n",
       "      <td>0.620109</td>\n",
       "      <td>0.547815</td>\n",
       "      <td>1.000000</td>\n",
       "      <td>0.512640</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>YearsWithCurrManager</th>\n",
       "      <td>-0.025553</td>\n",
       "      <td>0.204173</td>\n",
       "      <td>-0.163825</td>\n",
       "      <td>-0.002437</td>\n",
       "      <td>0.014304</td>\n",
       "      <td>0.063246</td>\n",
       "      <td>NaN</td>\n",
       "      <td>-0.025114</td>\n",
       "      <td>-0.008952</td>\n",
       "      <td>-0.021674</td>\n",
       "      <td>...</td>\n",
       "      <td>-0.000852</td>\n",
       "      <td>NaN</td>\n",
       "      <td>0.037954</td>\n",
       "      <td>0.461941</td>\n",
       "      <td>0.000387</td>\n",
       "      <td>0.002117</td>\n",
       "      <td>0.775746</td>\n",
       "      <td>0.703930</td>\n",
       "      <td>0.512640</td>\n",
       "      <td>1.000000</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "<p>28 rows × 28 columns</p>\n",
       "</div>"
      ],
      "text/plain": [
       "                           user_id       Age  Attrition  DailyRate  \\\n",
       "user_id                   1.000000  0.009300  -0.009329  -0.041355   \n",
       "Age                       0.009300  1.000000  -0.175754   0.016997   \n",
       "Attrition                -0.009329 -0.175754   1.000000  -0.065743   \n",
       "DailyRate                -0.041355  0.016997  -0.065743   1.000000   \n",
       "DistanceFromHome          0.029618 -0.006119   0.072157  -0.013230   \n",
       "Education                 0.058138  0.201116  -0.033683  -0.013333   \n",
       "EmployeeCount                  NaN       NaN        NaN        NaN   \n",
       "EmployeeNumber            0.999906  0.009602  -0.009786  -0.040680   \n",
       "EnvironmentSatisfaction   0.042355  0.016010  -0.095627   0.013415   \n",
       "HourlyRate                0.014785  0.035942  -0.003484   0.024577   \n",
       "JobInvolvement           -0.012119  0.043840  -0.114287   0.045446   \n",
       "JobLevel                 -0.009289  0.521973  -0.172917   0.004230   \n",
       "JobSatisfaction          -0.046578  0.003564  -0.098544   0.042196   \n",
       "MonthlyIncome            -0.004551  0.512036  -0.163906   0.010181   \n",
       "MonthlyRate               0.008913  0.009248   0.034358  -0.019472   \n",
       "NumCompaniesWorked        0.020461  0.321967   0.037556   0.020453   \n",
       "PercentSalaryHike        -0.010746  0.020275  -0.041065   0.020790   \n",
       "PerformanceRating        -0.020788  0.001435  -0.001920  -0.008661   \n",
       "RelationshipSatisfaction -0.064190  0.059735  -0.034985   0.000101   \n",
       "StandardHours                  NaN       NaN        NaN        NaN   \n",
       "StockOptionLevel          0.041794  0.045595  -0.129769   0.045414   \n",
       "TotalWorkingYears        -0.008958  0.686609  -0.181079   0.022416   \n",
       "TrainingTimesLastYear    -0.018542 -0.014888  -0.056043   0.000097   \n",
       "WorkLifeBalance           0.006358 -0.018682  -0.073935  -0.017483   \n",
       "YearsAtCompany           -0.019605  0.317604  -0.141555  -0.021911   \n",
       "YearsInCurrentRole       -0.019685  0.220128  -0.169024   0.027265   \n",
       "YearsSinceLastPromotion  -0.016308  0.213677  -0.042846  -0.015516   \n",
       "YearsWithCurrManager     -0.025553  0.204173  -0.163825  -0.002437   \n",
       "\n",
       "                          DistanceFromHome  Education  EmployeeCount  \\\n",
       "user_id                           0.029618   0.058138            NaN   \n",
       "Age                              -0.006119   0.201116            NaN   \n",
       "Attrition                         0.072157  -0.033683            NaN   \n",
       "DailyRate                        -0.013230  -0.013333            NaN   \n",
       "DistanceFromHome                  1.000000  -0.005039            NaN   \n",
       "Education                        -0.005039   1.000000            NaN   \n",
       "EmployeeCount                          NaN        NaN            NaN   \n",
       "EmployeeNumber                    0.029432   0.058453            NaN   \n",
       "EnvironmentSatisfaction          -0.013182  -0.038378            NaN   \n",
       "HourlyRate                        0.024524   0.004381            NaN   \n",
       "JobInvolvement                    0.020156   0.052512            NaN   \n",
       "JobLevel                          0.006961   0.106913            NaN   \n",
       "JobSatisfaction                   0.003149  -0.002777            NaN   \n",
       "MonthlyIncome                    -0.018398   0.103431            NaN   \n",
       "MonthlyRate                       0.009890  -0.039819            NaN   \n",
       "NumCompaniesWorked               -0.044021   0.127862            NaN   \n",
       "PercentSalaryHike                 0.024150  -0.025471            NaN   \n",
       "PerformanceRating                 0.020380  -0.043706            NaN   \n",
       "RelationshipSatisfaction          0.028912   0.000446            NaN   \n",
       "StandardHours                          NaN        NaN            NaN   \n",
       "StockOptionLevel                  0.056862   0.016850            NaN   \n",
       "TotalWorkingYears                -0.005337   0.148434            NaN   \n",
       "TrainingTimesLastYear            -0.051527  -0.016419            NaN   \n",
       "WorkLifeBalance                  -0.010663   0.026454            NaN   \n",
       "YearsAtCompany                   -0.003907   0.070153            NaN   \n",
       "YearsInCurrentRole                0.015311   0.063850            NaN   \n",
       "YearsSinceLastPromotion          -0.005778   0.043986            NaN   \n",
       "YearsWithCurrManager              0.014304   0.063246            NaN   \n",
       "\n",
       "                          EmployeeNumber  EnvironmentSatisfaction  HourlyRate  \\\n",
       "user_id                         0.999906                 0.042355    0.014785   \n",
       "Age                             0.009602                 0.016010    0.035942   \n",
       "Attrition                      -0.009786                -0.095627   -0.003484   \n",
       "DailyRate                      -0.040680                 0.013415    0.024577   \n",
       "DistanceFromHome                0.029432                -0.013182    0.024524   \n",
       "Education                       0.058453                -0.038378    0.004381   \n",
       "EmployeeCount                        NaN                      NaN         NaN   \n",
       "EmployeeNumber                  1.000000                 0.042183    0.015261   \n",
       "EnvironmentSatisfaction         0.042183                 1.000000   -0.048388   \n",
       "HourlyRate                      0.015261                -0.048388    1.000000   \n",
       "JobInvolvement                 -0.011711                 0.000299    0.070095   \n",
       "JobLevel                       -0.009964                 0.011368   -0.021629   \n",
       "JobSatisfaction                -0.046731                -0.016361   -0.065127   \n",
       "MonthlyIncome                  -0.005157                 0.004277   -0.014367   \n",
       "MonthlyRate                     0.009164                 0.030246   -0.024027   \n",
       "NumCompaniesWorked              0.019587                 0.010484    0.015841   \n",
       "PercentSalaryHike              -0.010404                -0.017302    0.008183   \n",
       "PerformanceRating              -0.020664                -0.014976    0.005624   \n",
       "RelationshipSatisfaction       -0.064441                 0.018885    0.008333   \n",
       "StandardHours                        NaN                      NaN         NaN   \n",
       "StockOptionLevel                0.041471                -0.002740    0.039087   \n",
       "TotalWorkingYears              -0.009325                -0.004375    0.000532   \n",
       "TrainingTimesLastYear          -0.018590                -0.014442   -0.023348   \n",
       "WorkLifeBalance                 0.005984                 0.038081   -0.012992   \n",
       "YearsAtCompany                 -0.019196                -0.003979   -0.011851   \n",
       "YearsInCurrentRole             -0.019196                 0.028714   -0.011254   \n",
       "YearsSinceLastPromotion        -0.016330                 0.016720   -0.001080   \n",
       "YearsWithCurrManager           -0.025114                -0.008952   -0.021674   \n",
       "\n",
       "                          ...  RelationshipSatisfaction  StandardHours  \\\n",
       "user_id                   ...                 -0.064190            NaN   \n",
       "Age                       ...                  0.059735            NaN   \n",
       "Attrition                 ...                 -0.034985            NaN   \n",
       "DailyRate                 ...                  0.000101            NaN   \n",
       "DistanceFromHome          ...                  0.028912            NaN   \n",
       "Education                 ...                  0.000446            NaN   \n",
       "EmployeeCount             ...                       NaN            NaN   \n",
       "EmployeeNumber            ...                 -0.064441            NaN   \n",
       "EnvironmentSatisfaction   ...                  0.018885            NaN   \n",
       "HourlyRate                ...                  0.008333            NaN   \n",
       "JobInvolvement            ...                  0.036821            NaN   \n",
       "JobLevel                  ...                  0.008952            NaN   \n",
       "JobSatisfaction           ...                 -0.023371            NaN   \n",
       "MonthlyIncome             ...                  0.008674            NaN   \n",
       "MonthlyRate               ...                 -0.015298            NaN   \n",
       "NumCompaniesWorked        ...                  0.059753            NaN   \n",
       "PercentSalaryHike         ...                 -0.035117            NaN   \n",
       "PerformanceRating         ...                 -0.029566            NaN   \n",
       "RelationshipSatisfaction  ...                  1.000000            NaN   \n",
       "StandardHours             ...                       NaN            NaN   \n",
       "StockOptionLevel          ...                 -0.026776            NaN   \n",
       "TotalWorkingYears         ...                  0.028391            NaN   \n",
       "TrainingTimesLastYear     ...                  0.015563            NaN   \n",
       "WorkLifeBalance           ...                  0.010885            NaN   \n",
       "YearsAtCompany            ...                  0.017059            NaN   \n",
       "YearsInCurrentRole        ...                 -0.023239            NaN   \n",
       "YearsSinceLastPromotion   ...                  0.030197            NaN   \n",
       "YearsWithCurrManager      ...                 -0.000852            NaN   \n",
       "\n",
       "                          StockOptionLevel  TotalWorkingYears  \\\n",
       "user_id                           0.041794          -0.008958   \n",
       "Age                               0.045595           0.686609   \n",
       "Attrition                        -0.129769          -0.181079   \n",
       "DailyRate                         0.045414           0.022416   \n",
       "DistanceFromHome                  0.056862          -0.005337   \n",
       "Education                         0.016850           0.148434   \n",
       "EmployeeCount                          NaN                NaN   \n",
       "EmployeeNumber                    0.041471          -0.009325   \n",
       "EnvironmentSatisfaction          -0.002740          -0.004375   \n",
       "HourlyRate                        0.039087           0.000532   \n",
       "JobInvolvement                    0.001249           0.023866   \n",
       "JobLevel                          0.030808           0.785153   \n",
       "JobSatisfaction                   0.031976          -0.022147   \n",
       "MonthlyIncome                     0.022962           0.774175   \n",
       "MonthlyRate                      -0.051149           0.021866   \n",
       "NumCompaniesWorked                0.024583           0.261906   \n",
       "PercentSalaryHike                 0.026610          -0.007065   \n",
       "PerformanceRating                 0.015025           0.010257   \n",
       "RelationshipSatisfaction         -0.026776           0.028391   \n",
       "StandardHours                          NaN                NaN   \n",
       "StockOptionLevel                  1.000000           0.026650   \n",
       "TotalWorkingYears                 0.026650           1.000000   \n",
       "TrainingTimesLastYear            -0.025434          -0.032999   \n",
       "WorkLifeBalance                   0.015246           0.001194   \n",
       "YearsAtCompany                    0.027250           0.634263   \n",
       "YearsInCurrentRole                0.056742           0.462848   \n",
       "YearsSinceLastPromotion           0.027216           0.409752   \n",
       "YearsWithCurrManager              0.037954           0.461941   \n",
       "\n",
       "                          TrainingTimesLastYear  WorkLifeBalance  \\\n",
       "user_id                               -0.018542         0.006358   \n",
       "Age                                   -0.014888        -0.018682   \n",
       "Attrition                             -0.056043        -0.073935   \n",
       "DailyRate                              0.000097        -0.017483   \n",
       "DistanceFromHome                      -0.051527        -0.010663   \n",
       "Education                             -0.016419         0.026454   \n",
       "EmployeeCount                               NaN              NaN   \n",
       "EmployeeNumber                        -0.018590         0.005984   \n",
       "EnvironmentSatisfaction               -0.014442         0.038081   \n",
       "HourlyRate                            -0.023348        -0.012992   \n",
       "JobInvolvement                        -0.037580        -0.022222   \n",
       "JobLevel                               0.002550         0.039172   \n",
       "JobSatisfaction                       -0.023552        -0.012945   \n",
       "MonthlyIncome                          0.000405         0.022595   \n",
       "MonthlyRate                           -0.004748         0.026192   \n",
       "NumCompaniesWorked                    -0.064855        -0.001043   \n",
       "PercentSalaryHike                     -0.010487        -0.008441   \n",
       "PerformanceRating                     -0.035685        -0.001030   \n",
       "RelationshipSatisfaction               0.015563         0.010885   \n",
       "StandardHours                               NaN              NaN   \n",
       "StockOptionLevel                      -0.025434         0.015246   \n",
       "TotalWorkingYears                     -0.032999         0.001194   \n",
       "TrainingTimesLastYear                  1.000000         0.019520   \n",
       "WorkLifeBalance                        0.019520         1.000000   \n",
       "YearsAtCompany                         0.011289         0.007255   \n",
       "YearsInCurrentRole                    -0.000465         0.055572   \n",
       "YearsSinceLastPromotion                0.016340         0.015814   \n",
       "YearsWithCurrManager                   0.000387         0.002117   \n",
       "\n",
       "                          YearsAtCompany  YearsInCurrentRole  \\\n",
       "user_id                        -0.019605           -0.019685   \n",
       "Age                             0.317604            0.220128   \n",
       "Attrition                      -0.141555           -0.169024   \n",
       "DailyRate                      -0.021911            0.027265   \n",
       "DistanceFromHome               -0.003907            0.015311   \n",
       "Education                       0.070153            0.063850   \n",
       "EmployeeCount                        NaN                 NaN   \n",
       "EmployeeNumber                 -0.019196           -0.019196   \n",
       "EnvironmentSatisfaction        -0.003979            0.028714   \n",
       "HourlyRate                     -0.011851           -0.011254   \n",
       "JobInvolvement                  0.004729            0.018510   \n",
       "JobLevel                        0.526776            0.381651   \n",
       "JobSatisfaction                -0.029844           -0.030511   \n",
       "MonthlyIncome                   0.511371            0.361812   \n",
       "MonthlyRate                    -0.026878           -0.008505   \n",
       "NumCompaniesWorked             -0.088854           -0.068468   \n",
       "PercentSalaryHike              -0.014789            0.031146   \n",
       "PerformanceRating               0.014116            0.051615   \n",
       "RelationshipSatisfaction        0.017059           -0.023239   \n",
       "StandardHours                        NaN                 NaN   \n",
       "StockOptionLevel                0.027250            0.056742   \n",
       "TotalWorkingYears               0.634263            0.462848   \n",
       "TrainingTimesLastYear           0.011289           -0.000465   \n",
       "WorkLifeBalance                 0.007255            0.055572   \n",
       "YearsAtCompany                  1.000000            0.752043   \n",
       "YearsInCurrentRole              0.752043            1.000000   \n",
       "YearsSinceLastPromotion         0.620109            0.547815   \n",
       "YearsWithCurrManager            0.775746            0.703930   \n",
       "\n",
       "                          YearsSinceLastPromotion  YearsWithCurrManager  \n",
       "user_id                                 -0.016308             -0.025553  \n",
       "Age                                      0.213677              0.204173  \n",
       "Attrition                               -0.042846             -0.163825  \n",
       "DailyRate                               -0.015516             -0.002437  \n",
       "DistanceFromHome                        -0.005778              0.014304  \n",
       "Education                                0.043986              0.063246  \n",
       "EmployeeCount                                 NaN                   NaN  \n",
       "EmployeeNumber                          -0.016330             -0.025114  \n",
       "EnvironmentSatisfaction                  0.016720             -0.008952  \n",
       "HourlyRate                              -0.001080             -0.021674  \n",
       "JobInvolvement                          -0.013330              0.036053  \n",
       "JobLevel                                 0.352960              0.368002  \n",
       "JobSatisfaction                         -0.049939             -0.049388  \n",
       "MonthlyIncome                            0.353480              0.339039  \n",
       "MonthlyRate                             -0.011861             -0.028764  \n",
       "NumCompaniesWorked                      -0.005041             -0.097412  \n",
       "PercentSalaryHike                       -0.014727              0.002441  \n",
       "PerformanceRating                        0.015243              0.023724  \n",
       "RelationshipSatisfaction                 0.030197             -0.000852  \n",
       "StandardHours                                 NaN                   NaN  \n",
       "StockOptionLevel                         0.027216              0.037954  \n",
       "TotalWorkingYears                        0.409752              0.461941  \n",
       "TrainingTimesLastYear                    0.016340              0.000387  \n",
       "WorkLifeBalance                          0.015814              0.002117  \n",
       "YearsAtCompany                           0.620109              0.775746  \n",
       "YearsInCurrentRole                       0.547815              0.703930  \n",
       "YearsSinceLastPromotion                  1.000000              0.512640  \n",
       "YearsWithCurrManager                     0.512640              1.000000  \n",
       "\n",
       "[28 rows x 28 columns]"
      ]
     },
     "execution_count": 32,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "train.corr()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 6,
   "metadata": {
    "collapsed": true,
    "jupyter": {
     "outputs_hidden": true
    }
   },
   "outputs": [
    {
     "ename": "AttributeError",
     "evalue": "'DataFrame' object has no attribute 'job'",
     "output_type": "error",
     "traceback": [
      "\u001b[1;31m---------------------------------------------------------------------------\u001b[0m",
      "\u001b[1;31mAttributeError\u001b[0m                            Traceback (most recent call last)",
      "\u001b[1;32m<ipython-input-6-c015bed4eca2>\u001b[0m in \u001b[0;36m<module>\u001b[1;34m\u001b[0m\n\u001b[1;32m----> 1\u001b[1;33m \u001b[0mtrain\u001b[0m\u001b[1;33m.\u001b[0m\u001b[0mjob\u001b[0m\u001b[1;33m.\u001b[0m\u001b[0mvalue_counts\u001b[0m\u001b[1;33m(\u001b[0m\u001b[1;33m)\u001b[0m\u001b[1;33m\u001b[0m\u001b[1;33m\u001b[0m\u001b[0m\n\u001b[0m",
      "\u001b[1;32md:\\学习\\研究生\\算法工程师\\bi\\bi_env\\lib\\site-packages\\pandas\\core\\generic.py\u001b[0m in \u001b[0;36m__getattr__\u001b[1;34m(self, name)\u001b[0m\n\u001b[0;32m   5272\u001b[0m             \u001b[1;32mif\u001b[0m \u001b[0mself\u001b[0m\u001b[1;33m.\u001b[0m\u001b[0m_info_axis\u001b[0m\u001b[1;33m.\u001b[0m\u001b[0m_can_hold_identifiers_and_holds_name\u001b[0m\u001b[1;33m(\u001b[0m\u001b[0mname\u001b[0m\u001b[1;33m)\u001b[0m\u001b[1;33m:\u001b[0m\u001b[1;33m\u001b[0m\u001b[1;33m\u001b[0m\u001b[0m\n\u001b[0;32m   5273\u001b[0m                 \u001b[1;32mreturn\u001b[0m \u001b[0mself\u001b[0m\u001b[1;33m[\u001b[0m\u001b[0mname\u001b[0m\u001b[1;33m]\u001b[0m\u001b[1;33m\u001b[0m\u001b[1;33m\u001b[0m\u001b[0m\n\u001b[1;32m-> 5274\u001b[1;33m             \u001b[1;32mreturn\u001b[0m \u001b[0mobject\u001b[0m\u001b[1;33m.\u001b[0m\u001b[0m__getattribute__\u001b[0m\u001b[1;33m(\u001b[0m\u001b[0mself\u001b[0m\u001b[1;33m,\u001b[0m \u001b[0mname\u001b[0m\u001b[1;33m)\u001b[0m\u001b[1;33m\u001b[0m\u001b[1;33m\u001b[0m\u001b[0m\n\u001b[0m\u001b[0;32m   5275\u001b[0m \u001b[1;33m\u001b[0m\u001b[0m\n\u001b[0;32m   5276\u001b[0m     \u001b[1;32mdef\u001b[0m \u001b[0m__setattr__\u001b[0m\u001b[1;33m(\u001b[0m\u001b[0mself\u001b[0m\u001b[1;33m,\u001b[0m \u001b[0mname\u001b[0m\u001b[1;33m:\u001b[0m \u001b[0mstr\u001b[0m\u001b[1;33m,\u001b[0m \u001b[0mvalue\u001b[0m\u001b[1;33m)\u001b[0m \u001b[1;33m->\u001b[0m \u001b[1;32mNone\u001b[0m\u001b[1;33m:\u001b[0m\u001b[1;33m\u001b[0m\u001b[1;33m\u001b[0m\u001b[0m\n",
      "\u001b[1;31mAttributeError\u001b[0m: 'DataFrame' object has no attribute 'job'"
     ]
    }
   ],
   "source": [
    "train.job.value_counts()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 12,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "(25317, 18)"
      ]
     },
     "execution_count": 12,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "train.shape"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 7,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "(1176, 36)"
      ]
     },
     "execution_count": 7,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "train.shape"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 13,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "(10852, 17)"
      ]
     },
     "execution_count": 13,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "test.shape"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 5,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/html": [
       "<div>\n",
       "<style scoped>\n",
       "    .dataframe tbody tr th:only-of-type {\n",
       "        vertical-align: middle;\n",
       "    }\n",
       "\n",
       "    .dataframe tbody tr th {\n",
       "        vertical-align: top;\n",
       "    }\n",
       "\n",
       "    .dataframe thead th {\n",
       "        text-align: right;\n",
       "    }\n",
       "</style>\n",
       "<table border=\"1\" class=\"dataframe\">\n",
       "  <thead>\n",
       "    <tr style=\"text-align: right;\">\n",
       "      <th></th>\n",
       "      <th>user_id</th>\n",
       "      <th>Age</th>\n",
       "      <th>Attrition</th>\n",
       "      <th>BusinessTravel</th>\n",
       "      <th>DailyRate</th>\n",
       "      <th>Department</th>\n",
       "      <th>DistanceFromHome</th>\n",
       "      <th>Education</th>\n",
       "      <th>EducationField</th>\n",
       "      <th>EmployeeCount</th>\n",
       "      <th>...</th>\n",
       "      <th>RelationshipSatisfaction</th>\n",
       "      <th>StandardHours</th>\n",
       "      <th>StockOptionLevel</th>\n",
       "      <th>TotalWorkingYears</th>\n",
       "      <th>TrainingTimesLastYear</th>\n",
       "      <th>WorkLifeBalance</th>\n",
       "      <th>YearsAtCompany</th>\n",
       "      <th>YearsInCurrentRole</th>\n",
       "      <th>YearsSinceLastPromotion</th>\n",
       "      <th>YearsWithCurrManager</th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th>0</th>\n",
       "      <td>1374</td>\n",
       "      <td>58</td>\n",
       "      <td>No</td>\n",
       "      <td>Travel_Rarely</td>\n",
       "      <td>605</td>\n",
       "      <td>Sales</td>\n",
       "      <td>21</td>\n",
       "      <td>3</td>\n",
       "      <td>Life Sciences</td>\n",
       "      <td>1</td>\n",
       "      <td>...</td>\n",
       "      <td>3</td>\n",
       "      <td>80</td>\n",
       "      <td>1</td>\n",
       "      <td>29</td>\n",
       "      <td>2</td>\n",
       "      <td>2</td>\n",
       "      <td>1</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>1</th>\n",
       "      <td>1092</td>\n",
       "      <td>45</td>\n",
       "      <td>No</td>\n",
       "      <td>Travel_Rarely</td>\n",
       "      <td>950</td>\n",
       "      <td>Research &amp; Development</td>\n",
       "      <td>28</td>\n",
       "      <td>3</td>\n",
       "      <td>Technical Degree</td>\n",
       "      <td>1</td>\n",
       "      <td>...</td>\n",
       "      <td>4</td>\n",
       "      <td>80</td>\n",
       "      <td>1</td>\n",
       "      <td>8</td>\n",
       "      <td>3</td>\n",
       "      <td>3</td>\n",
       "      <td>5</td>\n",
       "      <td>4</td>\n",
       "      <td>0</td>\n",
       "      <td>3</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2</th>\n",
       "      <td>768</td>\n",
       "      <td>40</td>\n",
       "      <td>No</td>\n",
       "      <td>Travel_Rarely</td>\n",
       "      <td>300</td>\n",
       "      <td>Sales</td>\n",
       "      <td>26</td>\n",
       "      <td>3</td>\n",
       "      <td>Marketing</td>\n",
       "      <td>1</td>\n",
       "      <td>...</td>\n",
       "      <td>2</td>\n",
       "      <td>80</td>\n",
       "      <td>1</td>\n",
       "      <td>8</td>\n",
       "      <td>3</td>\n",
       "      <td>2</td>\n",
       "      <td>7</td>\n",
       "      <td>7</td>\n",
       "      <td>7</td>\n",
       "      <td>5</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>3</th>\n",
       "      <td>569</td>\n",
       "      <td>36</td>\n",
       "      <td>No</td>\n",
       "      <td>Non-Travel</td>\n",
       "      <td>1434</td>\n",
       "      <td>Sales</td>\n",
       "      <td>8</td>\n",
       "      <td>4</td>\n",
       "      <td>Life Sciences</td>\n",
       "      <td>1</td>\n",
       "      <td>...</td>\n",
       "      <td>2</td>\n",
       "      <td>80</td>\n",
       "      <td>0</td>\n",
       "      <td>10</td>\n",
       "      <td>1</td>\n",
       "      <td>3</td>\n",
       "      <td>10</td>\n",
       "      <td>7</td>\n",
       "      <td>0</td>\n",
       "      <td>9</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>4</th>\n",
       "      <td>911</td>\n",
       "      <td>25</td>\n",
       "      <td>Yes</td>\n",
       "      <td>Travel_Frequently</td>\n",
       "      <td>599</td>\n",
       "      <td>Sales</td>\n",
       "      <td>24</td>\n",
       "      <td>1</td>\n",
       "      <td>Life Sciences</td>\n",
       "      <td>1</td>\n",
       "      <td>...</td>\n",
       "      <td>4</td>\n",
       "      <td>80</td>\n",
       "      <td>0</td>\n",
       "      <td>1</td>\n",
       "      <td>4</td>\n",
       "      <td>3</td>\n",
       "      <td>1</td>\n",
       "      <td>0</td>\n",
       "      <td>1</td>\n",
       "      <td>0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>...</th>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>1171</th>\n",
       "      <td>763</td>\n",
       "      <td>34</td>\n",
       "      <td>No</td>\n",
       "      <td>Travel_Rarely</td>\n",
       "      <td>1333</td>\n",
       "      <td>Sales</td>\n",
       "      <td>10</td>\n",
       "      <td>4</td>\n",
       "      <td>Life Sciences</td>\n",
       "      <td>1</td>\n",
       "      <td>...</td>\n",
       "      <td>4</td>\n",
       "      <td>80</td>\n",
       "      <td>1</td>\n",
       "      <td>1</td>\n",
       "      <td>2</td>\n",
       "      <td>3</td>\n",
       "      <td>1</td>\n",
       "      <td>1</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>1172</th>\n",
       "      <td>835</td>\n",
       "      <td>35</td>\n",
       "      <td>No</td>\n",
       "      <td>Travel_Rarely</td>\n",
       "      <td>528</td>\n",
       "      <td>Human Resources</td>\n",
       "      <td>8</td>\n",
       "      <td>4</td>\n",
       "      <td>Technical Degree</td>\n",
       "      <td>1</td>\n",
       "      <td>...</td>\n",
       "      <td>2</td>\n",
       "      <td>80</td>\n",
       "      <td>0</td>\n",
       "      <td>6</td>\n",
       "      <td>2</td>\n",
       "      <td>1</td>\n",
       "      <td>5</td>\n",
       "      <td>4</td>\n",
       "      <td>1</td>\n",
       "      <td>4</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>1173</th>\n",
       "      <td>1216</td>\n",
       "      <td>43</td>\n",
       "      <td>No</td>\n",
       "      <td>Travel_Rarely</td>\n",
       "      <td>1179</td>\n",
       "      <td>Sales</td>\n",
       "      <td>2</td>\n",
       "      <td>3</td>\n",
       "      <td>Medical</td>\n",
       "      <td>1</td>\n",
       "      <td>...</td>\n",
       "      <td>1</td>\n",
       "      <td>80</td>\n",
       "      <td>1</td>\n",
       "      <td>10</td>\n",
       "      <td>3</td>\n",
       "      <td>3</td>\n",
       "      <td>10</td>\n",
       "      <td>9</td>\n",
       "      <td>8</td>\n",
       "      <td>8</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>1174</th>\n",
       "      <td>559</td>\n",
       "      <td>38</td>\n",
       "      <td>No</td>\n",
       "      <td>Travel_Rarely</td>\n",
       "      <td>268</td>\n",
       "      <td>Research &amp; Development</td>\n",
       "      <td>2</td>\n",
       "      <td>5</td>\n",
       "      <td>Medical</td>\n",
       "      <td>1</td>\n",
       "      <td>...</td>\n",
       "      <td>2</td>\n",
       "      <td>80</td>\n",
       "      <td>1</td>\n",
       "      <td>6</td>\n",
       "      <td>0</td>\n",
       "      <td>1</td>\n",
       "      <td>1</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>1</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>1175</th>\n",
       "      <td>684</td>\n",
       "      <td>40</td>\n",
       "      <td>No</td>\n",
       "      <td>Travel_Rarely</td>\n",
       "      <td>658</td>\n",
       "      <td>Sales</td>\n",
       "      <td>10</td>\n",
       "      <td>4</td>\n",
       "      <td>Marketing</td>\n",
       "      <td>1</td>\n",
       "      <td>...</td>\n",
       "      <td>2</td>\n",
       "      <td>80</td>\n",
       "      <td>1</td>\n",
       "      <td>11</td>\n",
       "      <td>2</td>\n",
       "      <td>2</td>\n",
       "      <td>1</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "<p>1176 rows × 36 columns</p>\n",
       "</div>"
      ],
      "text/plain": [
       "      user_id  Age Attrition     BusinessTravel  DailyRate  \\\n",
       "0        1374   58        No      Travel_Rarely        605   \n",
       "1        1092   45        No      Travel_Rarely        950   \n",
       "2         768   40        No      Travel_Rarely        300   \n",
       "3         569   36        No         Non-Travel       1434   \n",
       "4         911   25       Yes  Travel_Frequently        599   \n",
       "...       ...  ...       ...                ...        ...   \n",
       "1171      763   34        No      Travel_Rarely       1333   \n",
       "1172      835   35        No      Travel_Rarely        528   \n",
       "1173     1216   43        No      Travel_Rarely       1179   \n",
       "1174      559   38        No      Travel_Rarely        268   \n",
       "1175      684   40        No      Travel_Rarely        658   \n",
       "\n",
       "                  Department  DistanceFromHome  Education    EducationField  \\\n",
       "0                      Sales                21          3     Life Sciences   \n",
       "1     Research & Development                28          3  Technical Degree   \n",
       "2                      Sales                26          3         Marketing   \n",
       "3                      Sales                 8          4     Life Sciences   \n",
       "4                      Sales                24          1     Life Sciences   \n",
       "...                      ...               ...        ...               ...   \n",
       "1171                   Sales                10          4     Life Sciences   \n",
       "1172         Human Resources                 8          4  Technical Degree   \n",
       "1173                   Sales                 2          3           Medical   \n",
       "1174  Research & Development                 2          5           Medical   \n",
       "1175                   Sales                10          4         Marketing   \n",
       "\n",
       "      EmployeeCount  ...  RelationshipSatisfaction  StandardHours  \\\n",
       "0                 1  ...                         3             80   \n",
       "1                 1  ...                         4             80   \n",
       "2                 1  ...                         2             80   \n",
       "3                 1  ...                         2             80   \n",
       "4                 1  ...                         4             80   \n",
       "...             ...  ...                       ...            ...   \n",
       "1171              1  ...                         4             80   \n",
       "1172              1  ...                         2             80   \n",
       "1173              1  ...                         1             80   \n",
       "1174              1  ...                         2             80   \n",
       "1175              1  ...                         2             80   \n",
       "\n",
       "     StockOptionLevel  TotalWorkingYears  TrainingTimesLastYear  \\\n",
       "0                   1                 29                      2   \n",
       "1                   1                  8                      3   \n",
       "2                   1                  8                      3   \n",
       "3                   0                 10                      1   \n",
       "4                   0                  1                      4   \n",
       "...               ...                ...                    ...   \n",
       "1171                1                  1                      2   \n",
       "1172                0                  6                      2   \n",
       "1173                1                 10                      3   \n",
       "1174                1                  6                      0   \n",
       "1175                1                 11                      2   \n",
       "\n",
       "      WorkLifeBalance YearsAtCompany  YearsInCurrentRole  \\\n",
       "0                   2              1                   0   \n",
       "1                   3              5                   4   \n",
       "2                   2              7                   7   \n",
       "3                   3             10                   7   \n",
       "4                   3              1                   0   \n",
       "...               ...            ...                 ...   \n",
       "1171                3              1                   1   \n",
       "1172                1              5                   4   \n",
       "1173                3             10                   9   \n",
       "1174                1              1                   0   \n",
       "1175                2              1                   0   \n",
       "\n",
       "     YearsSinceLastPromotion  YearsWithCurrManager  \n",
       "0                          0                     0  \n",
       "1                          0                     3  \n",
       "2                          7                     5  \n",
       "3                          0                     9  \n",
       "4                          1                     0  \n",
       "...                      ...                   ...  \n",
       "1171                       0                     0  \n",
       "1172                       1                     4  \n",
       "1173                       8                     8  \n",
       "1174                       0                     1  \n",
       "1175                       0                     0  \n",
       "\n",
       "[1176 rows x 36 columns]"
      ]
     },
     "execution_count": 5,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "train"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 3,
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "36\n"
     ]
    }
   ],
   "source": [
    "test['Attrition']=-1\n",
    "print(len(test.columns))"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 4,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "dtype('int64')"
      ]
     },
     "execution_count": 4,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "test.Attrition.dtype"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 4,
   "metadata": {},
   "outputs": [],
   "source": [
    "train.loc[train['Attrition']=='Yes','Attrition'] = 1"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 5,
   "metadata": {},
   "outputs": [],
   "source": [
    "train.loc[train['Attrition']=='No','Attrition'] = 0"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 6,
   "metadata": {},
   "outputs": [],
   "source": [
    "# data[i] = data[i].astype('category')\n",
    "train['Attrition'] = train['Attrition'].astype('int64')"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 7,
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "<class 'pandas.core.frame.DataFrame'>\n",
      "RangeIndex: 1176 entries, 0 to 1175\n",
      "Data columns (total 36 columns):\n",
      " #   Column                    Non-Null Count  Dtype \n",
      "---  ------                    --------------  ----- \n",
      " 0   user_id                   1176 non-null   int64 \n",
      " 1   Age                       1176 non-null   int64 \n",
      " 2   Attrition                 1176 non-null   int64 \n",
      " 3   BusinessTravel            1176 non-null   object\n",
      " 4   DailyRate                 1176 non-null   int64 \n",
      " 5   Department                1176 non-null   object\n",
      " 6   DistanceFromHome          1176 non-null   int64 \n",
      " 7   Education                 1176 non-null   int64 \n",
      " 8   EducationField            1176 non-null   object\n",
      " 9   EmployeeCount             1176 non-null   int64 \n",
      " 10  EmployeeNumber            1176 non-null   int64 \n",
      " 11  EnvironmentSatisfaction   1176 non-null   int64 \n",
      " 12  Gender                    1176 non-null   object\n",
      " 13  HourlyRate                1176 non-null   int64 \n",
      " 14  JobInvolvement            1176 non-null   int64 \n",
      " 15  JobLevel                  1176 non-null   int64 \n",
      " 16  JobRole                   1176 non-null   object\n",
      " 17  JobSatisfaction           1176 non-null   int64 \n",
      " 18  MaritalStatus             1176 non-null   object\n",
      " 19  MonthlyIncome             1176 non-null   int64 \n",
      " 20  MonthlyRate               1176 non-null   int64 \n",
      " 21  NumCompaniesWorked        1176 non-null   int64 \n",
      " 22  Over18                    1176 non-null   object\n",
      " 23  OverTime                  1176 non-null   object\n",
      " 24  PercentSalaryHike         1176 non-null   int64 \n",
      " 25  PerformanceRating         1176 non-null   int64 \n",
      " 26  RelationshipSatisfaction  1176 non-null   int64 \n",
      " 27  StandardHours             1176 non-null   int64 \n",
      " 28  StockOptionLevel          1176 non-null   int64 \n",
      " 29  TotalWorkingYears         1176 non-null   int64 \n",
      " 30  TrainingTimesLastYear     1176 non-null   int64 \n",
      " 31  WorkLifeBalance           1176 non-null   int64 \n",
      " 32  YearsAtCompany            1176 non-null   int64 \n",
      " 33  YearsInCurrentRole        1176 non-null   int64 \n",
      " 34  YearsSinceLastPromotion   1176 non-null   int64 \n",
      " 35  YearsWithCurrManager      1176 non-null   int64 \n",
      "dtypes: int64(28), object(8)\n",
      "memory usage: 330.9+ KB\n"
     ]
    }
   ],
   "source": [
    "train.info()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 7,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/html": [
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       "      <td>Research &amp; Development</td>\n",
       "      <td>28</td>\n",
       "      <td>3</td>\n",
       "      <td>Technical Degree</td>\n",
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       "      <td>4</td>\n",
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       "      <td>1</td>\n",
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       "      <th>2</th>\n",
       "      <td>768</td>\n",
       "      <td>40</td>\n",
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       "      <td>300</td>\n",
       "      <td>Sales</td>\n",
       "      <td>26</td>\n",
       "      <td>3</td>\n",
       "      <td>Marketing</td>\n",
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       "      <td>2</td>\n",
       "      <td>7</td>\n",
       "      <td>7</td>\n",
       "      <td>7</td>\n",
       "      <td>5</td>\n",
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       "      <th>3</th>\n",
       "      <td>569</td>\n",
       "      <td>36</td>\n",
       "      <td>0</td>\n",
       "      <td>Non-Travel</td>\n",
       "      <td>1434</td>\n",
       "      <td>Sales</td>\n",
       "      <td>8</td>\n",
       "      <td>4</td>\n",
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       "      <td>911</td>\n",
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       "      <td>Travel_Frequently</td>\n",
       "      <td>599</td>\n",
       "      <td>Sales</td>\n",
       "      <td>24</td>\n",
       "      <td>1</td>\n",
       "      <td>Life Sciences</td>\n",
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       "    <tr>\n",
       "      <th>...</th>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
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       "      <th>1465</th>\n",
       "      <td>1439</td>\n",
       "      <td>36</td>\n",
       "      <td>-1</td>\n",
       "      <td>Travel_Rarely</td>\n",
       "      <td>557</td>\n",
       "      <td>Sales</td>\n",
       "      <td>3</td>\n",
       "      <td>3</td>\n",
       "      <td>Medical</td>\n",
       "      <td>1</td>\n",
       "      <td>...</td>\n",
       "      <td>3</td>\n",
       "      <td>80</td>\n",
       "      <td>2</td>\n",
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       "      <td>9</td>\n",
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       "      <td>3</td>\n",
       "      <td>4</td>\n",
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       "    <tr>\n",
       "      <th>1466</th>\n",
       "      <td>481</td>\n",
       "      <td>34</td>\n",
       "      <td>-1</td>\n",
       "      <td>Travel_Rarely</td>\n",
       "      <td>254</td>\n",
       "      <td>Research &amp; Development</td>\n",
       "      <td>1</td>\n",
       "      <td>2</td>\n",
       "      <td>Life Sciences</td>\n",
       "      <td>1</td>\n",
       "      <td>...</td>\n",
       "      <td>4</td>\n",
       "      <td>80</td>\n",
       "      <td>1</td>\n",
       "      <td>6</td>\n",
       "      <td>3</td>\n",
       "      <td>3</td>\n",
       "      <td>6</td>\n",
       "      <td>5</td>\n",
       "      <td>1</td>\n",
       "      <td>3</td>\n",
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       "    <tr>\n",
       "      <th>1467</th>\n",
       "      <td>124</td>\n",
       "      <td>31</td>\n",
       "      <td>-1</td>\n",
       "      <td>Travel_Rarely</td>\n",
       "      <td>249</td>\n",
       "      <td>Sales</td>\n",
       "      <td>6</td>\n",
       "      <td>4</td>\n",
       "      <td>Life Sciences</td>\n",
       "      <td>1</td>\n",
       "      <td>...</td>\n",
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       "      <td>80</td>\n",
       "      <td>0</td>\n",
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       "      <td>7</td>\n",
       "      <td>7</td>\n",
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       "    <tr>\n",
       "      <th>1468</th>\n",
       "      <td>198</td>\n",
       "      <td>38</td>\n",
       "      <td>-1</td>\n",
       "      <td>Travel_Rarely</td>\n",
       "      <td>1261</td>\n",
       "      <td>Research &amp; Development</td>\n",
       "      <td>2</td>\n",
       "      <td>4</td>\n",
       "      <td>Life Sciences</td>\n",
       "      <td>1</td>\n",
       "      <td>...</td>\n",
       "      <td>2</td>\n",
       "      <td>80</td>\n",
       "      <td>0</td>\n",
       "      <td>14</td>\n",
       "      <td>3</td>\n",
       "      <td>3</td>\n",
       "      <td>1</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>1469</th>\n",
       "      <td>1229</td>\n",
       "      <td>40</td>\n",
       "      <td>-1</td>\n",
       "      <td>Travel_Rarely</td>\n",
       "      <td>369</td>\n",
       "      <td>Research &amp; Development</td>\n",
       "      <td>8</td>\n",
       "      <td>2</td>\n",
       "      <td>Life Sciences</td>\n",
       "      <td>1</td>\n",
       "      <td>...</td>\n",
       "      <td>2</td>\n",
       "      <td>80</td>\n",
       "      <td>1</td>\n",
       "      <td>18</td>\n",
       "      <td>3</td>\n",
       "      <td>3</td>\n",
       "      <td>1</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "<p>1470 rows × 36 columns</p>\n",
       "</div>"
      ],
      "text/plain": [
       "      user_id  Age  Attrition     BusinessTravel  DailyRate  \\\n",
       "0        1374   58          0      Travel_Rarely        605   \n",
       "1        1092   45          0      Travel_Rarely        950   \n",
       "2         768   40          0      Travel_Rarely        300   \n",
       "3         569   36          0         Non-Travel       1434   \n",
       "4         911   25          1  Travel_Frequently        599   \n",
       "...       ...  ...        ...                ...        ...   \n",
       "1465     1439   36         -1      Travel_Rarely        557   \n",
       "1466      481   34         -1      Travel_Rarely        254   \n",
       "1467      124   31         -1      Travel_Rarely        249   \n",
       "1468      198   38         -1      Travel_Rarely       1261   \n",
       "1469     1229   40         -1      Travel_Rarely        369   \n",
       "\n",
       "                  Department  DistanceFromHome  Education    EducationField  \\\n",
       "0                      Sales                21          3     Life Sciences   \n",
       "1     Research & Development                28          3  Technical Degree   \n",
       "2                      Sales                26          3         Marketing   \n",
       "3                      Sales                 8          4     Life Sciences   \n",
       "4                      Sales                24          1     Life Sciences   \n",
       "...                      ...               ...        ...               ...   \n",
       "1465                   Sales                 3          3           Medical   \n",
       "1466  Research & Development                 1          2     Life Sciences   \n",
       "1467                   Sales                 6          4     Life Sciences   \n",
       "1468  Research & Development                 2          4     Life Sciences   \n",
       "1469  Research & Development                 8          2     Life Sciences   \n",
       "\n",
       "      EmployeeCount  ...  RelationshipSatisfaction  StandardHours  \\\n",
       "0                 1  ...                         3             80   \n",
       "1                 1  ...                         4             80   \n",
       "2                 1  ...                         2             80   \n",
       "3                 1  ...                         2             80   \n",
       "4                 1  ...                         4             80   \n",
       "...             ...  ...                       ...            ...   \n",
       "1465              1  ...                         3             80   \n",
       "1466              1  ...                         4             80   \n",
       "1467              1  ...                         2             80   \n",
       "1468              1  ...                         2             80   \n",
       "1469              1  ...                         2             80   \n",
       "\n",
       "     StockOptionLevel  TotalWorkingYears  TrainingTimesLastYear  \\\n",
       "0                   1                 29                      2   \n",
       "1                   1                  8                      3   \n",
       "2                   1                  8                      3   \n",
       "3                   0                 10                      1   \n",
       "4                   0                  1                      4   \n",
       "...               ...                ...                    ...   \n",
       "1465                2                 10                      2   \n",
       "1466                1                  6                      3   \n",
       "1467                0                 12                      3   \n",
       "1468                0                 14                      3   \n",
       "1469                1                 18                      3   \n",
       "\n",
       "      WorkLifeBalance YearsAtCompany  YearsInCurrentRole  \\\n",
       "0                   2              1                   0   \n",
       "1                   3              5                   4   \n",
       "2                   2              7                   7   \n",
       "3                   3             10                   7   \n",
       "4                   3              1                   0   \n",
       "...               ...            ...                 ...   \n",
       "1465                3              9                   7   \n",
       "1466                3              6                   5   \n",
       "1467                2              7                   7   \n",
       "1468                3              1                   0   \n",
       "1469                3              1                   0   \n",
       "\n",
       "     YearsSinceLastPromotion  YearsWithCurrManager  \n",
       "0                          0                     0  \n",
       "1                          0                     3  \n",
       "2                          7                     5  \n",
       "3                          0                     9  \n",
       "4                          1                     0  \n",
       "...                      ...                   ...  \n",
       "1465                       3                     4  \n",
       "1466                       1                     3  \n",
       "1467                       7                     7  \n",
       "1468                       0                     0  \n",
       "1469                       0                     0  \n",
       "\n",
       "[1470 rows x 36 columns]"
      ]
     },
     "execution_count": 7,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "# data = train.append(test).reset_index(drop=True)\n",
    "data = pd.concat([train,test]).reset_index(drop=True)\n",
    "data"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 9,
   "metadata": {},
   "outputs": [],
   "source": [
    "data.drop(['EmployeeNumber'], axis=1, inplace=True)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 10,
   "metadata": {},
   "outputs": [],
   "source": [
    "data.drop(['StandardHours'], axis=1, inplace=True)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "metadata": {},
   "outputs": [],
   "source": []
  },
  {
   "cell_type": "code",
   "execution_count": 11,
   "metadata": {},
   "outputs": [
    {
     "data": {
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       "      <td>4</td>\n",
       "      <td>0</td>\n",
       "      <td>3</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2</th>\n",
       "      <td>768</td>\n",
       "      <td>40</td>\n",
       "      <td>0</td>\n",
       "      <td>Travel_Rarely</td>\n",
       "      <td>300</td>\n",
       "      <td>Sales</td>\n",
       "      <td>26</td>\n",
       "      <td>3</td>\n",
       "      <td>Marketing</td>\n",
       "      <td>1</td>\n",
       "      <td>...</td>\n",
       "      <td>3</td>\n",
       "      <td>2</td>\n",
       "      <td>1</td>\n",
       "      <td>8</td>\n",
       "      <td>3</td>\n",
       "      <td>2</td>\n",
       "      <td>7</td>\n",
       "      <td>7</td>\n",
       "      <td>7</td>\n",
       "      <td>5</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>3</th>\n",
       "      <td>569</td>\n",
       "      <td>36</td>\n",
       "      <td>0</td>\n",
       "      <td>Non-Travel</td>\n",
       "      <td>1434</td>\n",
       "      <td>Sales</td>\n",
       "      <td>8</td>\n",
       "      <td>4</td>\n",
       "      <td>Life Sciences</td>\n",
       "      <td>1</td>\n",
       "      <td>...</td>\n",
       "      <td>3</td>\n",
       "      <td>2</td>\n",
       "      <td>0</td>\n",
       "      <td>10</td>\n",
       "      <td>1</td>\n",
       "      <td>3</td>\n",
       "      <td>10</td>\n",
       "      <td>7</td>\n",
       "      <td>0</td>\n",
       "      <td>9</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>4</th>\n",
       "      <td>911</td>\n",
       "      <td>25</td>\n",
       "      <td>1</td>\n",
       "      <td>Travel_Frequently</td>\n",
       "      <td>599</td>\n",
       "      <td>Sales</td>\n",
       "      <td>24</td>\n",
       "      <td>1</td>\n",
       "      <td>Life Sciences</td>\n",
       "      <td>1</td>\n",
       "      <td>...</td>\n",
       "      <td>3</td>\n",
       "      <td>4</td>\n",
       "      <td>0</td>\n",
       "      <td>1</td>\n",
       "      <td>4</td>\n",
       "      <td>3</td>\n",
       "      <td>1</td>\n",
       "      <td>0</td>\n",
       "      <td>1</td>\n",
       "      <td>0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>...</th>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>1465</th>\n",
       "      <td>1439</td>\n",
       "      <td>36</td>\n",
       "      <td>-1</td>\n",
       "      <td>Travel_Rarely</td>\n",
       "      <td>557</td>\n",
       "      <td>Sales</td>\n",
       "      <td>3</td>\n",
       "      <td>3</td>\n",
       "      <td>Medical</td>\n",
       "      <td>1</td>\n",
       "      <td>...</td>\n",
       "      <td>3</td>\n",
       "      <td>3</td>\n",
       "      <td>2</td>\n",
       "      <td>10</td>\n",
       "      <td>2</td>\n",
       "      <td>3</td>\n",
       "      <td>9</td>\n",
       "      <td>7</td>\n",
       "      <td>3</td>\n",
       "      <td>4</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>1466</th>\n",
       "      <td>481</td>\n",
       "      <td>34</td>\n",
       "      <td>-1</td>\n",
       "      <td>Travel_Rarely</td>\n",
       "      <td>254</td>\n",
       "      <td>Research &amp; Development</td>\n",
       "      <td>1</td>\n",
       "      <td>2</td>\n",
       "      <td>Life Sciences</td>\n",
       "      <td>1</td>\n",
       "      <td>...</td>\n",
       "      <td>3</td>\n",
       "      <td>4</td>\n",
       "      <td>1</td>\n",
       "      <td>6</td>\n",
       "      <td>3</td>\n",
       "      <td>3</td>\n",
       "      <td>6</td>\n",
       "      <td>5</td>\n",
       "      <td>1</td>\n",
       "      <td>3</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>1467</th>\n",
       "      <td>124</td>\n",
       "      <td>31</td>\n",
       "      <td>-1</td>\n",
       "      <td>Travel_Rarely</td>\n",
       "      <td>249</td>\n",
       "      <td>Sales</td>\n",
       "      <td>6</td>\n",
       "      <td>4</td>\n",
       "      <td>Life Sciences</td>\n",
       "      <td>1</td>\n",
       "      <td>...</td>\n",
       "      <td>3</td>\n",
       "      <td>2</td>\n",
       "      <td>0</td>\n",
       "      <td>12</td>\n",
       "      <td>3</td>\n",
       "      <td>2</td>\n",
       "      <td>7</td>\n",
       "      <td>7</td>\n",
       "      <td>7</td>\n",
       "      <td>7</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>1468</th>\n",
       "      <td>198</td>\n",
       "      <td>38</td>\n",
       "      <td>-1</td>\n",
       "      <td>Travel_Rarely</td>\n",
       "      <td>1261</td>\n",
       "      <td>Research &amp; Development</td>\n",
       "      <td>2</td>\n",
       "      <td>4</td>\n",
       "      <td>Life Sciences</td>\n",
       "      <td>1</td>\n",
       "      <td>...</td>\n",
       "      <td>3</td>\n",
       "      <td>2</td>\n",
       "      <td>0</td>\n",
       "      <td>14</td>\n",
       "      <td>3</td>\n",
       "      <td>3</td>\n",
       "      <td>1</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>1469</th>\n",
       "      <td>1229</td>\n",
       "      <td>40</td>\n",
       "      <td>-1</td>\n",
       "      <td>Travel_Rarely</td>\n",
       "      <td>369</td>\n",
       "      <td>Research &amp; Development</td>\n",
       "      <td>8</td>\n",
       "      <td>2</td>\n",
       "      <td>Life Sciences</td>\n",
       "      <td>1</td>\n",
       "      <td>...</td>\n",
       "      <td>3</td>\n",
       "      <td>2</td>\n",
       "      <td>1</td>\n",
       "      <td>18</td>\n",
       "      <td>3</td>\n",
       "      <td>3</td>\n",
       "      <td>1</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "<p>1470 rows × 34 columns</p>\n",
       "</div>"
      ],
      "text/plain": [
       "      user_id  Age  Attrition     BusinessTravel  DailyRate  \\\n",
       "0        1374   58          0      Travel_Rarely        605   \n",
       "1        1092   45          0      Travel_Rarely        950   \n",
       "2         768   40          0      Travel_Rarely        300   \n",
       "3         569   36          0         Non-Travel       1434   \n",
       "4         911   25          1  Travel_Frequently        599   \n",
       "...       ...  ...        ...                ...        ...   \n",
       "1465     1439   36         -1      Travel_Rarely        557   \n",
       "1466      481   34         -1      Travel_Rarely        254   \n",
       "1467      124   31         -1      Travel_Rarely        249   \n",
       "1468      198   38         -1      Travel_Rarely       1261   \n",
       "1469     1229   40         -1      Travel_Rarely        369   \n",
       "\n",
       "                  Department  DistanceFromHome  Education    EducationField  \\\n",
       "0                      Sales                21          3     Life Sciences   \n",
       "1     Research & Development                28          3  Technical Degree   \n",
       "2                      Sales                26          3         Marketing   \n",
       "3                      Sales                 8          4     Life Sciences   \n",
       "4                      Sales                24          1     Life Sciences   \n",
       "...                      ...               ...        ...               ...   \n",
       "1465                   Sales                 3          3           Medical   \n",
       "1466  Research & Development                 1          2     Life Sciences   \n",
       "1467                   Sales                 6          4     Life Sciences   \n",
       "1468  Research & Development                 2          4     Life Sciences   \n",
       "1469  Research & Development                 8          2     Life Sciences   \n",
       "\n",
       "      EmployeeCount  ...  PerformanceRating RelationshipSatisfaction  \\\n",
       "0                 1  ...                  3                        3   \n",
       "1                 1  ...                  4                        4   \n",
       "2                 1  ...                  3                        2   \n",
       "3                 1  ...                  3                        2   \n",
       "4                 1  ...                  3                        4   \n",
       "...             ...  ...                ...                      ...   \n",
       "1465              1  ...                  3                        3   \n",
       "1466              1  ...                  3                        4   \n",
       "1467              1  ...                  3                        2   \n",
       "1468              1  ...                  3                        2   \n",
       "1469              1  ...                  3                        2   \n",
       "\n",
       "      StockOptionLevel  TotalWorkingYears  TrainingTimesLastYear  \\\n",
       "0                    1                 29                      2   \n",
       "1                    1                  8                      3   \n",
       "2                    1                  8                      3   \n",
       "3                    0                 10                      1   \n",
       "4                    0                  1                      4   \n",
       "...                ...                ...                    ...   \n",
       "1465                 2                 10                      2   \n",
       "1466                 1                  6                      3   \n",
       "1467                 0                 12                      3   \n",
       "1468                 0                 14                      3   \n",
       "1469                 1                 18                      3   \n",
       "\n",
       "     WorkLifeBalance  YearsAtCompany YearsInCurrentRole  \\\n",
       "0                  2               1                  0   \n",
       "1                  3               5                  4   \n",
       "2                  2               7                  7   \n",
       "3                  3              10                  7   \n",
       "4                  3               1                  0   \n",
       "...              ...             ...                ...   \n",
       "1465               3               9                  7   \n",
       "1466               3               6                  5   \n",
       "1467               2               7                  7   \n",
       "1468               3               1                  0   \n",
       "1469               3               1                  0   \n",
       "\n",
       "      YearsSinceLastPromotion  YearsWithCurrManager  \n",
       "0                           0                     0  \n",
       "1                           0                     3  \n",
       "2                           7                     5  \n",
       "3                           0                     9  \n",
       "4                           1                     0  \n",
       "...                       ...                   ...  \n",
       "1465                        3                     4  \n",
       "1466                        1                     3  \n",
       "1467                        7                     7  \n",
       "1468                        0                     0  \n",
       "1469                        0                     0  \n",
       "\n",
       "[1470 rows x 34 columns]"
      ]
     },
     "execution_count": 11,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "data"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 46,
   "metadata": {
    "collapsed": true,
    "jupyter": {
     "outputs_hidden": true
    }
   },
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "<class 'pandas.core.frame.DataFrame'>\n",
      "RangeIndex: 1470 entries, 0 to 1469\n",
      "Data columns (total 36 columns):\n",
      " #   Column                    Non-Null Count  Dtype \n",
      "---  ------                    --------------  ----- \n",
      " 0   user_id                   1470 non-null   int64 \n",
      " 1   Age                       1470 non-null   int64 \n",
      " 2   Attrition                 1470 non-null   int64 \n",
      " 3   BusinessTravel            1470 non-null   object\n",
      " 4   DailyRate                 1470 non-null   int64 \n",
      " 5   Department                1470 non-null   object\n",
      " 6   DistanceFromHome          1470 non-null   int64 \n",
      " 7   Education                 1470 non-null   int64 \n",
      " 8   EducationField            1470 non-null   object\n",
      " 9   EmployeeCount             1470 non-null   int64 \n",
      " 10  EmployeeNumber            1470 non-null   int64 \n",
      " 11  EnvironmentSatisfaction   1470 non-null   int64 \n",
      " 12  Gender                    1470 non-null   object\n",
      " 13  HourlyRate                1470 non-null   int64 \n",
      " 14  JobInvolvement            1470 non-null   int64 \n",
      " 15  JobLevel                  1470 non-null   int64 \n",
      " 16  JobRole                   1470 non-null   object\n",
      " 17  JobSatisfaction           1470 non-null   int64 \n",
      " 18  MaritalStatus             1470 non-null   object\n",
      " 19  MonthlyIncome             1470 non-null   int64 \n",
      " 20  MonthlyRate               1470 non-null   int64 \n",
      " 21  NumCompaniesWorked        1470 non-null   int64 \n",
      " 22  Over18                    1470 non-null   object\n",
      " 23  OverTime                  1470 non-null   object\n",
      " 24  PercentSalaryHike         1470 non-null   int64 \n",
      " 25  PerformanceRating         1470 non-null   int64 \n",
      " 26  RelationshipSatisfaction  1470 non-null   int64 \n",
      " 27  StandardHours             1470 non-null   int64 \n",
      " 28  StockOptionLevel          1470 non-null   int64 \n",
      " 29  TotalWorkingYears         1470 non-null   int64 \n",
      " 30  TrainingTimesLastYear     1470 non-null   int64 \n",
      " 31  WorkLifeBalance           1470 non-null   int64 \n",
      " 32  YearsAtCompany            1470 non-null   int64 \n",
      " 33  YearsInCurrentRole        1470 non-null   int64 \n",
      " 34  YearsSinceLastPromotion   1470 non-null   int64 \n",
      " 35  YearsWithCurrManager      1470 non-null   int64 \n",
      "dtypes: int64(28), object(8)\n",
      "memory usage: 413.6+ KB\n"
     ]
    }
   ],
   "source": [
    "data.info()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 8,
   "metadata": {},
   "outputs": [],
   "source": [
    "path='./'\n",
    "import os\n",
    "import json\n",
    "import gc\n",
    "# os.system('pip install numba')\n",
    "from numba import jit\n",
    "#tqdm\n",
    "# os.system('pip install tqdm')\n",
    "from tqdm import tqdm_notebook\n",
    "from tqdm import tqdm\n",
    "\n",
    "#Integrated model\n",
    "# os.system('pip install lightgbm')\n",
    "import lightgbm as lgb\n",
    "# os.system('pip install catboost==0.15.2')\n",
    "import catboost as cbt\n",
    "# os.system('pip install xgboost')\n",
    "# import xgboost as xgb\n",
    "\n",
    "#base import \n",
    "import numpy as np\n",
    "import pandas as pd\n",
    "\n",
    "# about sklearn\n",
    "from sklearn.metrics import roc_auc_score\n",
    "from sklearn.model_selection import StratifiedKFold, KFold, RepeatedKFold\n",
    "from sklearn.preprocessing import LabelEncoder\n",
    "from sklearn.preprocessing import StandardScaler\n",
    "from sklearn.metrics import mean_absolute_error\n",
    "from sklearn.linear_model import LinearRegression\n",
    "from sklearn.preprocessing import StandardScaler as std\n",
    "from sklearn.kernel_ridge import KernelRidge\n",
    "from sklearn.metrics import f1_score\n",
    "#about time\n",
    "import time\n",
    "import datetime \n",
    "from datetime import datetime, timedelta\n",
    "\n",
    "#Garbage collection\n",
    "import gc\n",
    "# scipy\n",
    "from scipy.signal import hilbert\n",
    "from scipy.signal import hann\n",
    "from scipy.signal import convolve\n",
    "from scipy import stats\n",
    "import scipy.spatial.distance as dist\n",
    "#other\n",
    "from collections import Counter \n",
    "from statistics import mode \n",
    "    #warning\n",
    "import warnings\n",
    "warnings.filterwarnings(\"ignore\")\n",
    "import json \n",
    "import math\n",
    "from itertools import product\n",
    "import ast "
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 13,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/html": [
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       "    .dataframe tbody tr th {\n",
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       "</style>\n",
       "<table border=\"1\" class=\"dataframe\">\n",
       "  <thead>\n",
       "    <tr style=\"text-align: right;\">\n",
       "      <th></th>\n",
       "      <th>user_id</th>\n",
       "      <th>Age</th>\n",
       "      <th>Attrition</th>\n",
       "      <th>BusinessTravel</th>\n",
       "      <th>DailyRate</th>\n",
       "      <th>Department</th>\n",
       "      <th>DistanceFromHome</th>\n",
       "      <th>Education</th>\n",
       "      <th>EducationField</th>\n",
       "      <th>EmployeeCount</th>\n",
       "      <th>...</th>\n",
       "      <th>PerformanceRating</th>\n",
       "      <th>RelationshipSatisfaction</th>\n",
       "      <th>StockOptionLevel</th>\n",
       "      <th>TotalWorkingYears</th>\n",
       "      <th>TrainingTimesLastYear</th>\n",
       "      <th>WorkLifeBalance</th>\n",
       "      <th>YearsAtCompany</th>\n",
       "      <th>YearsInCurrentRole</th>\n",
       "      <th>YearsSinceLastPromotion</th>\n",
       "      <th>YearsWithCurrManager</th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th>0</th>\n",
       "      <td>1374</td>\n",
       "      <td>58</td>\n",
       "      <td>0</td>\n",
       "      <td>Travel_Rarely</td>\n",
       "      <td>605</td>\n",
       "      <td>Sales</td>\n",
       "      <td>21</td>\n",
       "      <td>3</td>\n",
       "      <td>Life Sciences</td>\n",
       "      <td>1</td>\n",
       "      <td>...</td>\n",
       "      <td>3</td>\n",
       "      <td>3</td>\n",
       "      <td>1</td>\n",
       "      <td>29</td>\n",
       "      <td>2</td>\n",
       "      <td>2</td>\n",
       "      <td>1</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>1</th>\n",
       "      <td>1092</td>\n",
       "      <td>45</td>\n",
       "      <td>0</td>\n",
       "      <td>Travel_Rarely</td>\n",
       "      <td>950</td>\n",
       "      <td>Research &amp; Development</td>\n",
       "      <td>28</td>\n",
       "      <td>3</td>\n",
       "      <td>Technical Degree</td>\n",
       "      <td>1</td>\n",
       "      <td>...</td>\n",
       "      <td>4</td>\n",
       "      <td>4</td>\n",
       "      <td>1</td>\n",
       "      <td>8</td>\n",
       "      <td>3</td>\n",
       "      <td>3</td>\n",
       "      <td>5</td>\n",
       "      <td>4</td>\n",
       "      <td>0</td>\n",
       "      <td>3</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2</th>\n",
       "      <td>768</td>\n",
       "      <td>40</td>\n",
       "      <td>0</td>\n",
       "      <td>Travel_Rarely</td>\n",
       "      <td>300</td>\n",
       "      <td>Sales</td>\n",
       "      <td>26</td>\n",
       "      <td>3</td>\n",
       "      <td>Marketing</td>\n",
       "      <td>1</td>\n",
       "      <td>...</td>\n",
       "      <td>3</td>\n",
       "      <td>2</td>\n",
       "      <td>1</td>\n",
       "      <td>8</td>\n",
       "      <td>3</td>\n",
       "      <td>2</td>\n",
       "      <td>7</td>\n",
       "      <td>7</td>\n",
       "      <td>7</td>\n",
       "      <td>5</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>3</th>\n",
       "      <td>569</td>\n",
       "      <td>36</td>\n",
       "      <td>0</td>\n",
       "      <td>Non-Travel</td>\n",
       "      <td>1434</td>\n",
       "      <td>Sales</td>\n",
       "      <td>8</td>\n",
       "      <td>4</td>\n",
       "      <td>Life Sciences</td>\n",
       "      <td>1</td>\n",
       "      <td>...</td>\n",
       "      <td>3</td>\n",
       "      <td>2</td>\n",
       "      <td>0</td>\n",
       "      <td>10</td>\n",
       "      <td>1</td>\n",
       "      <td>3</td>\n",
       "      <td>10</td>\n",
       "      <td>7</td>\n",
       "      <td>0</td>\n",
       "      <td>9</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>4</th>\n",
       "      <td>911</td>\n",
       "      <td>25</td>\n",
       "      <td>1</td>\n",
       "      <td>Travel_Frequently</td>\n",
       "      <td>599</td>\n",
       "      <td>Sales</td>\n",
       "      <td>24</td>\n",
       "      <td>1</td>\n",
       "      <td>Life Sciences</td>\n",
       "      <td>1</td>\n",
       "      <td>...</td>\n",
       "      <td>3</td>\n",
       "      <td>4</td>\n",
       "      <td>0</td>\n",
       "      <td>1</td>\n",
       "      <td>4</td>\n",
       "      <td>3</td>\n",
       "      <td>1</td>\n",
       "      <td>0</td>\n",
       "      <td>1</td>\n",
       "      <td>0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>...</th>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>1465</th>\n",
       "      <td>1439</td>\n",
       "      <td>36</td>\n",
       "      <td>-1</td>\n",
       "      <td>Travel_Rarely</td>\n",
       "      <td>557</td>\n",
       "      <td>Sales</td>\n",
       "      <td>3</td>\n",
       "      <td>3</td>\n",
       "      <td>Medical</td>\n",
       "      <td>1</td>\n",
       "      <td>...</td>\n",
       "      <td>3</td>\n",
       "      <td>3</td>\n",
       "      <td>2</td>\n",
       "      <td>10</td>\n",
       "      <td>2</td>\n",
       "      <td>3</td>\n",
       "      <td>9</td>\n",
       "      <td>7</td>\n",
       "      <td>3</td>\n",
       "      <td>4</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>1466</th>\n",
       "      <td>481</td>\n",
       "      <td>34</td>\n",
       "      <td>-1</td>\n",
       "      <td>Travel_Rarely</td>\n",
       "      <td>254</td>\n",
       "      <td>Research &amp; Development</td>\n",
       "      <td>1</td>\n",
       "      <td>2</td>\n",
       "      <td>Life Sciences</td>\n",
       "      <td>1</td>\n",
       "      <td>...</td>\n",
       "      <td>3</td>\n",
       "      <td>4</td>\n",
       "      <td>1</td>\n",
       "      <td>6</td>\n",
       "      <td>3</td>\n",
       "      <td>3</td>\n",
       "      <td>6</td>\n",
       "      <td>5</td>\n",
       "      <td>1</td>\n",
       "      <td>3</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>1467</th>\n",
       "      <td>124</td>\n",
       "      <td>31</td>\n",
       "      <td>-1</td>\n",
       "      <td>Travel_Rarely</td>\n",
       "      <td>249</td>\n",
       "      <td>Sales</td>\n",
       "      <td>6</td>\n",
       "      <td>4</td>\n",
       "      <td>Life Sciences</td>\n",
       "      <td>1</td>\n",
       "      <td>...</td>\n",
       "      <td>3</td>\n",
       "      <td>2</td>\n",
       "      <td>0</td>\n",
       "      <td>12</td>\n",
       "      <td>3</td>\n",
       "      <td>2</td>\n",
       "      <td>7</td>\n",
       "      <td>7</td>\n",
       "      <td>7</td>\n",
       "      <td>7</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>1468</th>\n",
       "      <td>198</td>\n",
       "      <td>38</td>\n",
       "      <td>-1</td>\n",
       "      <td>Travel_Rarely</td>\n",
       "      <td>1261</td>\n",
       "      <td>Research &amp; Development</td>\n",
       "      <td>2</td>\n",
       "      <td>4</td>\n",
       "      <td>Life Sciences</td>\n",
       "      <td>1</td>\n",
       "      <td>...</td>\n",
       "      <td>3</td>\n",
       "      <td>2</td>\n",
       "      <td>0</td>\n",
       "      <td>14</td>\n",
       "      <td>3</td>\n",
       "      <td>3</td>\n",
       "      <td>1</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>1469</th>\n",
       "      <td>1229</td>\n",
       "      <td>40</td>\n",
       "      <td>-1</td>\n",
       "      <td>Travel_Rarely</td>\n",
       "      <td>369</td>\n",
       "      <td>Research &amp; Development</td>\n",
       "      <td>8</td>\n",
       "      <td>2</td>\n",
       "      <td>Life Sciences</td>\n",
       "      <td>1</td>\n",
       "      <td>...</td>\n",
       "      <td>3</td>\n",
       "      <td>2</td>\n",
       "      <td>1</td>\n",
       "      <td>18</td>\n",
       "      <td>3</td>\n",
       "      <td>3</td>\n",
       "      <td>1</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "<p>1470 rows × 34 columns</p>\n",
       "</div>"
      ],
      "text/plain": [
       "      user_id  Age  Attrition     BusinessTravel  DailyRate  \\\n",
       "0        1374   58          0      Travel_Rarely        605   \n",
       "1        1092   45          0      Travel_Rarely        950   \n",
       "2         768   40          0      Travel_Rarely        300   \n",
       "3         569   36          0         Non-Travel       1434   \n",
       "4         911   25          1  Travel_Frequently        599   \n",
       "...       ...  ...        ...                ...        ...   \n",
       "1465     1439   36         -1      Travel_Rarely        557   \n",
       "1466      481   34         -1      Travel_Rarely        254   \n",
       "1467      124   31         -1      Travel_Rarely        249   \n",
       "1468      198   38         -1      Travel_Rarely       1261   \n",
       "1469     1229   40         -1      Travel_Rarely        369   \n",
       "\n",
       "                  Department  DistanceFromHome  Education    EducationField  \\\n",
       "0                      Sales                21          3     Life Sciences   \n",
       "1     Research & Development                28          3  Technical Degree   \n",
       "2                      Sales                26          3         Marketing   \n",
       "3                      Sales                 8          4     Life Sciences   \n",
       "4                      Sales                24          1     Life Sciences   \n",
       "...                      ...               ...        ...               ...   \n",
       "1465                   Sales                 3          3           Medical   \n",
       "1466  Research & Development                 1          2     Life Sciences   \n",
       "1467                   Sales                 6          4     Life Sciences   \n",
       "1468  Research & Development                 2          4     Life Sciences   \n",
       "1469  Research & Development                 8          2     Life Sciences   \n",
       "\n",
       "      EmployeeCount  ...  PerformanceRating RelationshipSatisfaction  \\\n",
       "0                 1  ...                  3                        3   \n",
       "1                 1  ...                  4                        4   \n",
       "2                 1  ...                  3                        2   \n",
       "3                 1  ...                  3                        2   \n",
       "4                 1  ...                  3                        4   \n",
       "...             ...  ...                ...                      ...   \n",
       "1465              1  ...                  3                        3   \n",
       "1466              1  ...                  3                        4   \n",
       "1467              1  ...                  3                        2   \n",
       "1468              1  ...                  3                        2   \n",
       "1469              1  ...                  3                        2   \n",
       "\n",
       "      StockOptionLevel  TotalWorkingYears  TrainingTimesLastYear  \\\n",
       "0                    1                 29                      2   \n",
       "1                    1                  8                      3   \n",
       "2                    1                  8                      3   \n",
       "3                    0                 10                      1   \n",
       "4                    0                  1                      4   \n",
       "...                ...                ...                    ...   \n",
       "1465                 2                 10                      2   \n",
       "1466                 1                  6                      3   \n",
       "1467                 0                 12                      3   \n",
       "1468                 0                 14                      3   \n",
       "1469                 1                 18                      3   \n",
       "\n",
       "     WorkLifeBalance  YearsAtCompany YearsInCurrentRole  \\\n",
       "0                  2               1                  0   \n",
       "1                  3               5                  4   \n",
       "2                  2               7                  7   \n",
       "3                  3              10                  7   \n",
       "4                  3               1                  0   \n",
       "...              ...             ...                ...   \n",
       "1465               3               9                  7   \n",
       "1466               3               6                  5   \n",
       "1467               2               7                  7   \n",
       "1468               3               1                  0   \n",
       "1469               3               1                  0   \n",
       "\n",
       "      YearsSinceLastPromotion  YearsWithCurrManager  \n",
       "0                           0                     0  \n",
       "1                           0                     3  \n",
       "2                           7                     5  \n",
       "3                           0                     9  \n",
       "4                           1                     0  \n",
       "...                       ...                   ...  \n",
       "1465                        3                     4  \n",
       "1466                        1                     3  \n",
       "1467                        7                     7  \n",
       "1468                        0                     0  \n",
       "1469                        0                     0  \n",
       "\n",
       "[1470 rows x 34 columns]"
      ]
     },
     "execution_count": 13,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "data"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 9,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "application/vnd.jupyter.widget-view+json": {
       "model_id": "591fd712c0b74623b125dfb1f1c3b651",
       "version_major": 2,
       "version_minor": 0
      },
      "text/plain": [
       "HBox(children=(FloatProgress(value=0.0, max=8.0), HTML(value='')))"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "\n"
     ]
    }
   ],
   "source": [
    "cat_col = [i for i in data.select_dtypes(object).columns if i not in ['user_id','Attrition']]\n",
    "\n",
    "for i in tqdm_notebook(cat_col):\n",
    "    lbl = LabelEncoder()\n",
    "# #     data['count_' + i] = data.groupby([i])[i].transform('count')\n",
    "    data[i] = lbl.fit_transform(data[i].astype(str))"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 15,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/html": [
       "<div>\n",
       "<style scoped>\n",
       "    .dataframe tbody tr th:only-of-type {\n",
       "        vertical-align: middle;\n",
       "    }\n",
       "\n",
       "    .dataframe tbody tr th {\n",
       "        vertical-align: top;\n",
       "    }\n",
       "\n",
       "    .dataframe thead th {\n",
       "        text-align: right;\n",
       "    }\n",
       "</style>\n",
       "<table border=\"1\" class=\"dataframe\">\n",
       "  <thead>\n",
       "    <tr style=\"text-align: right;\">\n",
       "      <th></th>\n",
       "      <th>user_id</th>\n",
       "      <th>Age</th>\n",
       "      <th>Attrition</th>\n",
       "      <th>BusinessTravel</th>\n",
       "      <th>DailyRate</th>\n",
       "      <th>Department</th>\n",
       "      <th>DistanceFromHome</th>\n",
       "      <th>Education</th>\n",
       "      <th>EducationField</th>\n",
       "      <th>EmployeeCount</th>\n",
       "      <th>...</th>\n",
       "      <th>PerformanceRating</th>\n",
       "      <th>RelationshipSatisfaction</th>\n",
       "      <th>StockOptionLevel</th>\n",
       "      <th>TotalWorkingYears</th>\n",
       "      <th>TrainingTimesLastYear</th>\n",
       "      <th>WorkLifeBalance</th>\n",
       "      <th>YearsAtCompany</th>\n",
       "      <th>YearsInCurrentRole</th>\n",
       "      <th>YearsSinceLastPromotion</th>\n",
       "      <th>YearsWithCurrManager</th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th>0</th>\n",
       "      <td>1374</td>\n",
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       "      <td>0</td>\n",
       "      <td>2</td>\n",
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       "      <td>21</td>\n",
       "      <td>3</td>\n",
       "      <td>1</td>\n",
       "      <td>1</td>\n",
       "      <td>...</td>\n",
       "      <td>3</td>\n",
       "      <td>3</td>\n",
       "      <td>1</td>\n",
       "      <td>29</td>\n",
       "      <td>2</td>\n",
       "      <td>2</td>\n",
       "      <td>1</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>1</th>\n",
       "      <td>1092</td>\n",
       "      <td>45</td>\n",
       "      <td>0</td>\n",
       "      <td>2</td>\n",
       "      <td>950</td>\n",
       "      <td>1</td>\n",
       "      <td>28</td>\n",
       "      <td>3</td>\n",
       "      <td>5</td>\n",
       "      <td>1</td>\n",
       "      <td>...</td>\n",
       "      <td>4</td>\n",
       "      <td>4</td>\n",
       "      <td>1</td>\n",
       "      <td>8</td>\n",
       "      <td>3</td>\n",
       "      <td>3</td>\n",
       "      <td>5</td>\n",
       "      <td>4</td>\n",
       "      <td>0</td>\n",
       "      <td>3</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2</th>\n",
       "      <td>768</td>\n",
       "      <td>40</td>\n",
       "      <td>0</td>\n",
       "      <td>2</td>\n",
       "      <td>300</td>\n",
       "      <td>2</td>\n",
       "      <td>26</td>\n",
       "      <td>3</td>\n",
       "      <td>2</td>\n",
       "      <td>1</td>\n",
       "      <td>...</td>\n",
       "      <td>3</td>\n",
       "      <td>2</td>\n",
       "      <td>1</td>\n",
       "      <td>8</td>\n",
       "      <td>3</td>\n",
       "      <td>2</td>\n",
       "      <td>7</td>\n",
       "      <td>7</td>\n",
       "      <td>7</td>\n",
       "      <td>5</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>3</th>\n",
       "      <td>569</td>\n",
       "      <td>36</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>1434</td>\n",
       "      <td>2</td>\n",
       "      <td>8</td>\n",
       "      <td>4</td>\n",
       "      <td>1</td>\n",
       "      <td>1</td>\n",
       "      <td>...</td>\n",
       "      <td>3</td>\n",
       "      <td>2</td>\n",
       "      <td>0</td>\n",
       "      <td>10</td>\n",
       "      <td>1</td>\n",
       "      <td>3</td>\n",
       "      <td>10</td>\n",
       "      <td>7</td>\n",
       "      <td>0</td>\n",
       "      <td>9</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>4</th>\n",
       "      <td>911</td>\n",
       "      <td>25</td>\n",
       "      <td>1</td>\n",
       "      <td>1</td>\n",
       "      <td>599</td>\n",
       "      <td>2</td>\n",
       "      <td>24</td>\n",
       "      <td>1</td>\n",
       "      <td>1</td>\n",
       "      <td>1</td>\n",
       "      <td>...</td>\n",
       "      <td>3</td>\n",
       "      <td>4</td>\n",
       "      <td>0</td>\n",
       "      <td>1</td>\n",
       "      <td>4</td>\n",
       "      <td>3</td>\n",
       "      <td>1</td>\n",
       "      <td>0</td>\n",
       "      <td>1</td>\n",
       "      <td>0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>...</th>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>1465</th>\n",
       "      <td>1439</td>\n",
       "      <td>36</td>\n",
       "      <td>-1</td>\n",
       "      <td>2</td>\n",
       "      <td>557</td>\n",
       "      <td>2</td>\n",
       "      <td>3</td>\n",
       "      <td>3</td>\n",
       "      <td>3</td>\n",
       "      <td>1</td>\n",
       "      <td>...</td>\n",
       "      <td>3</td>\n",
       "      <td>3</td>\n",
       "      <td>2</td>\n",
       "      <td>10</td>\n",
       "      <td>2</td>\n",
       "      <td>3</td>\n",
       "      <td>9</td>\n",
       "      <td>7</td>\n",
       "      <td>3</td>\n",
       "      <td>4</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>1466</th>\n",
       "      <td>481</td>\n",
       "      <td>34</td>\n",
       "      <td>-1</td>\n",
       "      <td>2</td>\n",
       "      <td>254</td>\n",
       "      <td>1</td>\n",
       "      <td>1</td>\n",
       "      <td>2</td>\n",
       "      <td>1</td>\n",
       "      <td>1</td>\n",
       "      <td>...</td>\n",
       "      <td>3</td>\n",
       "      <td>4</td>\n",
       "      <td>1</td>\n",
       "      <td>6</td>\n",
       "      <td>3</td>\n",
       "      <td>3</td>\n",
       "      <td>6</td>\n",
       "      <td>5</td>\n",
       "      <td>1</td>\n",
       "      <td>3</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>1467</th>\n",
       "      <td>124</td>\n",
       "      <td>31</td>\n",
       "      <td>-1</td>\n",
       "      <td>2</td>\n",
       "      <td>249</td>\n",
       "      <td>2</td>\n",
       "      <td>6</td>\n",
       "      <td>4</td>\n",
       "      <td>1</td>\n",
       "      <td>1</td>\n",
       "      <td>...</td>\n",
       "      <td>3</td>\n",
       "      <td>2</td>\n",
       "      <td>0</td>\n",
       "      <td>12</td>\n",
       "      <td>3</td>\n",
       "      <td>2</td>\n",
       "      <td>7</td>\n",
       "      <td>7</td>\n",
       "      <td>7</td>\n",
       "      <td>7</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>1468</th>\n",
       "      <td>198</td>\n",
       "      <td>38</td>\n",
       "      <td>-1</td>\n",
       "      <td>2</td>\n",
       "      <td>1261</td>\n",
       "      <td>1</td>\n",
       "      <td>2</td>\n",
       "      <td>4</td>\n",
       "      <td>1</td>\n",
       "      <td>1</td>\n",
       "      <td>...</td>\n",
       "      <td>3</td>\n",
       "      <td>2</td>\n",
       "      <td>0</td>\n",
       "      <td>14</td>\n",
       "      <td>3</td>\n",
       "      <td>3</td>\n",
       "      <td>1</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>1469</th>\n",
       "      <td>1229</td>\n",
       "      <td>40</td>\n",
       "      <td>-1</td>\n",
       "      <td>2</td>\n",
       "      <td>369</td>\n",
       "      <td>1</td>\n",
       "      <td>8</td>\n",
       "      <td>2</td>\n",
       "      <td>1</td>\n",
       "      <td>1</td>\n",
       "      <td>...</td>\n",
       "      <td>3</td>\n",
       "      <td>2</td>\n",
       "      <td>1</td>\n",
       "      <td>18</td>\n",
       "      <td>3</td>\n",
       "      <td>3</td>\n",
       "      <td>1</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "<p>1470 rows × 34 columns</p>\n",
       "</div>"
      ],
      "text/plain": [
       "      user_id  Age  Attrition  BusinessTravel  DailyRate  Department  \\\n",
       "0        1374   58          0               2        605           2   \n",
       "1        1092   45          0               2        950           1   \n",
       "2         768   40          0               2        300           2   \n",
       "3         569   36          0               0       1434           2   \n",
       "4         911   25          1               1        599           2   \n",
       "...       ...  ...        ...             ...        ...         ...   \n",
       "1465     1439   36         -1               2        557           2   \n",
       "1466      481   34         -1               2        254           1   \n",
       "1467      124   31         -1               2        249           2   \n",
       "1468      198   38         -1               2       1261           1   \n",
       "1469     1229   40         -1               2        369           1   \n",
       "\n",
       "      DistanceFromHome  Education  EducationField  EmployeeCount  ...  \\\n",
       "0                   21          3               1              1  ...   \n",
       "1                   28          3               5              1  ...   \n",
       "2                   26          3               2              1  ...   \n",
       "3                    8          4               1              1  ...   \n",
       "4                   24          1               1              1  ...   \n",
       "...                ...        ...             ...            ...  ...   \n",
       "1465                 3          3               3              1  ...   \n",
       "1466                 1          2               1              1  ...   \n",
       "1467                 6          4               1              1  ...   \n",
       "1468                 2          4               1              1  ...   \n",
       "1469                 8          2               1              1  ...   \n",
       "\n",
       "      PerformanceRating  RelationshipSatisfaction  StockOptionLevel  \\\n",
       "0                     3                         3                 1   \n",
       "1                     4                         4                 1   \n",
       "2                     3                         2                 1   \n",
       "3                     3                         2                 0   \n",
       "4                     3                         4                 0   \n",
       "...                 ...                       ...               ...   \n",
       "1465                  3                         3                 2   \n",
       "1466                  3                         4                 1   \n",
       "1467                  3                         2                 0   \n",
       "1468                  3                         2                 0   \n",
       "1469                  3                         2                 1   \n",
       "\n",
       "      TotalWorkingYears  TrainingTimesLastYear  WorkLifeBalance  \\\n",
       "0                    29                      2                2   \n",
       "1                     8                      3                3   \n",
       "2                     8                      3                2   \n",
       "3                    10                      1                3   \n",
       "4                     1                      4                3   \n",
       "...                 ...                    ...              ...   \n",
       "1465                 10                      2                3   \n",
       "1466                  6                      3                3   \n",
       "1467                 12                      3                2   \n",
       "1468                 14                      3                3   \n",
       "1469                 18                      3                3   \n",
       "\n",
       "      YearsAtCompany  YearsInCurrentRole  YearsSinceLastPromotion  \\\n",
       "0                  1                   0                        0   \n",
       "1                  5                   4                        0   \n",
       "2                  7                   7                        7   \n",
       "3                 10                   7                        0   \n",
       "4                  1                   0                        1   \n",
       "...              ...                 ...                      ...   \n",
       "1465               9                   7                        3   \n",
       "1466               6                   5                        1   \n",
       "1467               7                   7                        7   \n",
       "1468               1                   0                        0   \n",
       "1469               1                   0                        0   \n",
       "\n",
       "      YearsWithCurrManager  \n",
       "0                        0  \n",
       "1                        3  \n",
       "2                        5  \n",
       "3                        9  \n",
       "4                        0  \n",
       "...                    ...  \n",
       "1465                     4  \n",
       "1466                     3  \n",
       "1467                     7  \n",
       "1468                     0  \n",
       "1469                     0  \n",
       "\n",
       "[1470 rows x 34 columns]"
      ]
     },
     "execution_count": 15,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "data"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 11,
   "metadata": {},
   "outputs": [],
   "source": [
    "# for i in cat_col:\n",
    "#     data[i] = data[i].astype('category')"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 10,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "['Age',\n",
       " 'BusinessTravel',\n",
       " 'DailyRate',\n",
       " 'Department',\n",
       " 'DistanceFromHome',\n",
       " 'Education',\n",
       " 'EducationField',\n",
       " 'EmployeeCount',\n",
       " 'EmployeeNumber',\n",
       " 'EnvironmentSatisfaction',\n",
       " 'Gender',\n",
       " 'HourlyRate',\n",
       " 'JobInvolvement',\n",
       " 'JobLevel',\n",
       " 'JobRole',\n",
       " 'JobSatisfaction',\n",
       " 'MaritalStatus',\n",
       " 'MonthlyIncome',\n",
       " 'MonthlyRate',\n",
       " 'NumCompaniesWorked',\n",
       " 'Over18',\n",
       " 'OverTime',\n",
       " 'PercentSalaryHike',\n",
       " 'PerformanceRating',\n",
       " 'RelationshipSatisfaction',\n",
       " 'StandardHours',\n",
       " 'StockOptionLevel',\n",
       " 'TotalWorkingYears',\n",
       " 'TrainingTimesLastYear',\n",
       " 'WorkLifeBalance',\n",
       " 'YearsAtCompany',\n",
       " 'YearsInCurrentRole',\n",
       " 'YearsSinceLastPromotion',\n",
       " 'YearsWithCurrManager']"
      ]
     },
     "execution_count": 10,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "feats = [i for i in data.columns if i not in ['user_id','Attrition']]\n",
    "feats"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 11,
   "metadata": {},
   "outputs": [],
   "source": [
    "import numpy as np\n",
    "\n",
    "max_min_scaler = lambda x : (x-np.min(x))/(np.max(x)-np.min(x))\n",
    "for i in feats:\n",
    "    data[i]=data[[i]].apply(max_min_scaler)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 19,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/html": [
       "<div>\n",
       "<style scoped>\n",
       "    .dataframe tbody tr th:only-of-type {\n",
       "        vertical-align: middle;\n",
       "    }\n",
       "\n",
       "    .dataframe tbody tr th {\n",
       "        vertical-align: top;\n",
       "    }\n",
       "\n",
       "    .dataframe thead th {\n",
       "        text-align: right;\n",
       "    }\n",
       "</style>\n",
       "<table border=\"1\" class=\"dataframe\">\n",
       "  <thead>\n",
       "    <tr style=\"text-align: right;\">\n",
       "      <th></th>\n",
       "      <th>user_id</th>\n",
       "      <th>Age</th>\n",
       "      <th>Attrition</th>\n",
       "      <th>BusinessTravel</th>\n",
       "      <th>DailyRate</th>\n",
       "      <th>Department</th>\n",
       "      <th>DistanceFromHome</th>\n",
       "      <th>Education</th>\n",
       "      <th>EducationField</th>\n",
       "      <th>EmployeeCount</th>\n",
       "      <th>...</th>\n",
       "      <th>PerformanceRating</th>\n",
       "      <th>RelationshipSatisfaction</th>\n",
       "      <th>StockOptionLevel</th>\n",
       "      <th>TotalWorkingYears</th>\n",
       "      <th>TrainingTimesLastYear</th>\n",
       "      <th>WorkLifeBalance</th>\n",
       "      <th>YearsAtCompany</th>\n",
       "      <th>YearsInCurrentRole</th>\n",
       "      <th>YearsSinceLastPromotion</th>\n",
       "      <th>YearsWithCurrManager</th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th>0</th>\n",
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       "      <td>0.50</td>\n",
       "      <td>0.2</td>\n",
       "      <td>NaN</td>\n",
       "      <td>...</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.666667</td>\n",
       "      <td>0.333333</td>\n",
       "      <td>0.725</td>\n",
       "      <td>0.333333</td>\n",
       "      <td>0.333333</td>\n",
       "      <td>0.025</td>\n",
       "      <td>0.000000</td>\n",
       "      <td>0.000000</td>\n",
       "      <td>0.000000</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>1</th>\n",
       "      <td>1092</td>\n",
       "      <td>0.642857</td>\n",
       "      <td>0</td>\n",
       "      <td>1.0</td>\n",
       "      <td>0.607015</td>\n",
       "      <td>0.5</td>\n",
       "      <td>0.964286</td>\n",
       "      <td>0.50</td>\n",
       "      <td>1.0</td>\n",
       "      <td>NaN</td>\n",
       "      <td>...</td>\n",
       "      <td>1.0</td>\n",
       "      <td>1.000000</td>\n",
       "      <td>0.333333</td>\n",
       "      <td>0.200</td>\n",
       "      <td>0.500000</td>\n",
       "      <td>0.666667</td>\n",
       "      <td>0.125</td>\n",
       "      <td>0.222222</td>\n",
       "      <td>0.000000</td>\n",
       "      <td>0.176471</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2</th>\n",
       "      <td>768</td>\n",
       "      <td>0.523810</td>\n",
       "      <td>0</td>\n",
       "      <td>1.0</td>\n",
       "      <td>0.141732</td>\n",
       "      <td>1.0</td>\n",
       "      <td>0.892857</td>\n",
       "      <td>0.50</td>\n",
       "      <td>0.4</td>\n",
       "      <td>NaN</td>\n",
       "      <td>...</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.333333</td>\n",
       "      <td>0.333333</td>\n",
       "      <td>0.200</td>\n",
       "      <td>0.500000</td>\n",
       "      <td>0.333333</td>\n",
       "      <td>0.175</td>\n",
       "      <td>0.388889</td>\n",
       "      <td>0.466667</td>\n",
       "      <td>0.294118</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>3</th>\n",
       "      <td>569</td>\n",
       "      <td>0.428571</td>\n",
       "      <td>0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.953472</td>\n",
       "      <td>1.0</td>\n",
       "      <td>0.250000</td>\n",
       "      <td>0.75</td>\n",
       "      <td>0.2</td>\n",
       "      <td>NaN</td>\n",
       "      <td>...</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.333333</td>\n",
       "      <td>0.000000</td>\n",
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       "      <td>0.166667</td>\n",
       "      <td>0.666667</td>\n",
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       "      <td>0.388889</td>\n",
       "      <td>0.000000</td>\n",
       "      <td>0.529412</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>4</th>\n",
       "      <td>911</td>\n",
       "      <td>0.166667</td>\n",
       "      <td>1</td>\n",
       "      <td>0.5</td>\n",
       "      <td>0.355762</td>\n",
       "      <td>1.0</td>\n",
       "      <td>0.821429</td>\n",
       "      <td>0.00</td>\n",
       "      <td>0.2</td>\n",
       "      <td>NaN</td>\n",
       "      <td>...</td>\n",
       "      <td>0.0</td>\n",
       "      <td>1.000000</td>\n",
       "      <td>0.000000</td>\n",
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       "      <td>0.666667</td>\n",
       "      <td>0.025</td>\n",
       "      <td>0.000000</td>\n",
       "      <td>0.066667</td>\n",
       "      <td>0.000000</td>\n",
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       "    <tr>\n",
       "      <th>...</th>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
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       "    <tr>\n",
       "      <th>1465</th>\n",
       "      <td>1439</td>\n",
       "      <td>0.428571</td>\n",
       "      <td>-1</td>\n",
       "      <td>1.0</td>\n",
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       "      <td>1.0</td>\n",
       "      <td>0.071429</td>\n",
       "      <td>0.50</td>\n",
       "      <td>0.6</td>\n",
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       "      <td>...</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.666667</td>\n",
       "      <td>0.666667</td>\n",
       "      <td>0.250</td>\n",
       "      <td>0.333333</td>\n",
       "      <td>0.666667</td>\n",
       "      <td>0.225</td>\n",
       "      <td>0.388889</td>\n",
       "      <td>0.200000</td>\n",
       "      <td>0.235294</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>1466</th>\n",
       "      <td>481</td>\n",
       "      <td>0.380952</td>\n",
       "      <td>-1</td>\n",
       "      <td>1.0</td>\n",
       "      <td>0.108805</td>\n",
       "      <td>0.5</td>\n",
       "      <td>0.000000</td>\n",
       "      <td>0.25</td>\n",
       "      <td>0.2</td>\n",
       "      <td>NaN</td>\n",
       "      <td>...</td>\n",
       "      <td>0.0</td>\n",
       "      <td>1.000000</td>\n",
       "      <td>0.333333</td>\n",
       "      <td>0.150</td>\n",
       "      <td>0.500000</td>\n",
       "      <td>0.666667</td>\n",
       "      <td>0.150</td>\n",
       "      <td>0.277778</td>\n",
       "      <td>0.066667</td>\n",
       "      <td>0.176471</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>1467</th>\n",
       "      <td>124</td>\n",
       "      <td>0.309524</td>\n",
       "      <td>-1</td>\n",
       "      <td>1.0</td>\n",
       "      <td>0.105225</td>\n",
       "      <td>1.0</td>\n",
       "      <td>0.178571</td>\n",
       "      <td>0.75</td>\n",
       "      <td>0.2</td>\n",
       "      <td>NaN</td>\n",
       "      <td>...</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.333333</td>\n",
       "      <td>0.000000</td>\n",
       "      <td>0.300</td>\n",
       "      <td>0.500000</td>\n",
       "      <td>0.333333</td>\n",
       "      <td>0.175</td>\n",
       "      <td>0.388889</td>\n",
       "      <td>0.466667</td>\n",
       "      <td>0.411765</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>1468</th>\n",
       "      <td>198</td>\n",
       "      <td>0.476190</td>\n",
       "      <td>-1</td>\n",
       "      <td>1.0</td>\n",
       "      <td>0.829635</td>\n",
       "      <td>0.5</td>\n",
       "      <td>0.035714</td>\n",
       "      <td>0.75</td>\n",
       "      <td>0.2</td>\n",
       "      <td>NaN</td>\n",
       "      <td>...</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.333333</td>\n",
       "      <td>0.000000</td>\n",
       "      <td>0.350</td>\n",
       "      <td>0.500000</td>\n",
       "      <td>0.666667</td>\n",
       "      <td>0.025</td>\n",
       "      <td>0.000000</td>\n",
       "      <td>0.000000</td>\n",
       "      <td>0.000000</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>1469</th>\n",
       "      <td>1229</td>\n",
       "      <td>0.523810</td>\n",
       "      <td>-1</td>\n",
       "      <td>1.0</td>\n",
       "      <td>0.191124</td>\n",
       "      <td>0.5</td>\n",
       "      <td>0.250000</td>\n",
       "      <td>0.25</td>\n",
       "      <td>0.2</td>\n",
       "      <td>NaN</td>\n",
       "      <td>...</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.333333</td>\n",
       "      <td>0.333333</td>\n",
       "      <td>0.450</td>\n",
       "      <td>0.500000</td>\n",
       "      <td>0.666667</td>\n",
       "      <td>0.025</td>\n",
       "      <td>0.000000</td>\n",
       "      <td>0.000000</td>\n",
       "      <td>0.000000</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "<p>1470 rows × 34 columns</p>\n",
       "</div>"
      ],
      "text/plain": [
       "      user_id       Age  Attrition  BusinessTravel  DailyRate  Department  \\\n",
       "0        1374  0.952381          0             1.0   0.360057         1.0   \n",
       "1        1092  0.642857          0             1.0   0.607015         0.5   \n",
       "2         768  0.523810          0             1.0   0.141732         1.0   \n",
       "3         569  0.428571          0             0.0   0.953472         1.0   \n",
       "4         911  0.166667          1             0.5   0.355762         1.0   \n",
       "...       ...       ...        ...             ...        ...         ...   \n",
       "1465     1439  0.428571         -1             1.0   0.325698         1.0   \n",
       "1466      481  0.380952         -1             1.0   0.108805         0.5   \n",
       "1467      124  0.309524         -1             1.0   0.105225         1.0   \n",
       "1468      198  0.476190         -1             1.0   0.829635         0.5   \n",
       "1469     1229  0.523810         -1             1.0   0.191124         0.5   \n",
       "\n",
       "      DistanceFromHome  Education  EducationField  EmployeeCount  ...  \\\n",
       "0             0.714286       0.50             0.2            NaN  ...   \n",
       "1             0.964286       0.50             1.0            NaN  ...   \n",
       "2             0.892857       0.50             0.4            NaN  ...   \n",
       "3             0.250000       0.75             0.2            NaN  ...   \n",
       "4             0.821429       0.00             0.2            NaN  ...   \n",
       "...                ...        ...             ...            ...  ...   \n",
       "1465          0.071429       0.50             0.6            NaN  ...   \n",
       "1466          0.000000       0.25             0.2            NaN  ...   \n",
       "1467          0.178571       0.75             0.2            NaN  ...   \n",
       "1468          0.035714       0.75             0.2            NaN  ...   \n",
       "1469          0.250000       0.25             0.2            NaN  ...   \n",
       "\n",
       "      PerformanceRating  RelationshipSatisfaction  StockOptionLevel  \\\n",
       "0                   0.0                  0.666667          0.333333   \n",
       "1                   1.0                  1.000000          0.333333   \n",
       "2                   0.0                  0.333333          0.333333   \n",
       "3                   0.0                  0.333333          0.000000   \n",
       "4                   0.0                  1.000000          0.000000   \n",
       "...                 ...                       ...               ...   \n",
       "1465                0.0                  0.666667          0.666667   \n",
       "1466                0.0                  1.000000          0.333333   \n",
       "1467                0.0                  0.333333          0.000000   \n",
       "1468                0.0                  0.333333          0.000000   \n",
       "1469                0.0                  0.333333          0.333333   \n",
       "\n",
       "      TotalWorkingYears  TrainingTimesLastYear  WorkLifeBalance  \\\n",
       "0                 0.725               0.333333         0.333333   \n",
       "1                 0.200               0.500000         0.666667   \n",
       "2                 0.200               0.500000         0.333333   \n",
       "3                 0.250               0.166667         0.666667   \n",
       "4                 0.025               0.666667         0.666667   \n",
       "...                 ...                    ...              ...   \n",
       "1465              0.250               0.333333         0.666667   \n",
       "1466              0.150               0.500000         0.666667   \n",
       "1467              0.300               0.500000         0.333333   \n",
       "1468              0.350               0.500000         0.666667   \n",
       "1469              0.450               0.500000         0.666667   \n",
       "\n",
       "      YearsAtCompany  YearsInCurrentRole  YearsSinceLastPromotion  \\\n",
       "0              0.025            0.000000                 0.000000   \n",
       "1              0.125            0.222222                 0.000000   \n",
       "2              0.175            0.388889                 0.466667   \n",
       "3              0.250            0.388889                 0.000000   \n",
       "4              0.025            0.000000                 0.066667   \n",
       "...              ...                 ...                      ...   \n",
       "1465           0.225            0.388889                 0.200000   \n",
       "1466           0.150            0.277778                 0.066667   \n",
       "1467           0.175            0.388889                 0.466667   \n",
       "1468           0.025            0.000000                 0.000000   \n",
       "1469           0.025            0.000000                 0.000000   \n",
       "\n",
       "      YearsWithCurrManager  \n",
       "0                 0.000000  \n",
       "1                 0.176471  \n",
       "2                 0.294118  \n",
       "3                 0.529412  \n",
       "4                 0.000000  \n",
       "...                    ...  \n",
       "1465              0.235294  \n",
       "1466              0.176471  \n",
       "1467              0.411765  \n",
       "1468              0.000000  \n",
       "1469              0.000000  \n",
       "\n",
       "[1470 rows x 34 columns]"
      ]
     },
     "execution_count": 19,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "data"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 12,
   "metadata": {},
   "outputs": [],
   "source": [
    "from xgboost import XGBClassifier\n",
    "\n",
    "model = XGBClassifier(learning_rate=0.08,\n",
    "                      n_estimators=300,         # 树的个数--300棵树建立xgboost\n",
    "                      max_depth=3,               # 树的深度\n",
    "                      min_child_weight = 1,      # 叶子节点最小权重\n",
    "                      gamma=0.3,                  # 惩罚项中叶子结点个数前的参数\n",
    "                      subsample=0.8,             # 随机选择80%样本建立决策树\n",
    "                      colsample_btree=0.8,       # 随机选择80%特征建立决策树\n",
    "                      objective='binary:logistic', # 指定损失函数\n",
    "                      scale_pos_weight=1,        # 解决样本个数不平衡的问题\n",
    "                      random_state=27            # 随机数\n",
    "                      )"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 13,
   "metadata": {},
   "outputs": [],
   "source": [
    "data1 =data[data['Attrition']!=-1][feats]\n",
    "label1 =data[data['Attrition']!=-1]['Attrition']\n",
    "testx= data[data['Attrition']==-1][feats]"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 19,
   "metadata": {
    "collapsed": true,
    "jupyter": {
     "outputs_hidden": true
    }
   },
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "[11:28:01] WARNING: C:\\Users\\Administrator\\workspace\\xgboost-win64_release_1.1.0\\src\\learner.cc:480: \n",
      "Parameters: { colsample_btree } might not be used.\n",
      "\n",
      "  This may not be accurate due to some parameters are only used in language bindings but\n",
      "  passed down to XGBoost core.  Or some parameters are not used but slip through this\n",
      "  verification. Please open an issue if you find above cases.\n",
      "\n",
      "\n",
      "[0]\tvalidation_0-auc:0.75490\tvalidation_1-auc:0.69628\n",
      "Multiple eval metrics have been passed: 'validation_1-auc' will be used for early stopping.\n",
      "\n",
      "Will train until validation_1-auc hasn't improved in 231 rounds.\n",
      "[1]\tvalidation_0-auc:0.77260\tvalidation_1-auc:0.73796\n",
      "[2]\tvalidation_0-auc:0.78946\tvalidation_1-auc:0.74182\n",
      "[3]\tvalidation_0-auc:0.82248\tvalidation_1-auc:0.75013\n",
      "[4]\tvalidation_0-auc:0.83086\tvalidation_1-auc:0.74847\n",
      "[5]\tvalidation_0-auc:0.84447\tvalidation_1-auc:0.74604\n",
      "[6]\tvalidation_0-auc:0.84752\tvalidation_1-auc:0.75029\n",
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      "[9]\tvalidation_0-auc:0.86816\tvalidation_1-auc:0.76687\n",
      "[10]\tvalidation_0-auc:0.86854\tvalidation_1-auc:0.76520\n",
      "[11]\tvalidation_0-auc:0.87418\tvalidation_1-auc:0.76708\n",
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      "[18]\tvalidation_0-auc:0.89744\tvalidation_1-auc:0.77043\n",
      "[19]\tvalidation_0-auc:0.89743\tvalidation_1-auc:0.77033\n",
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      "[30]\tvalidation_0-auc:0.91710\tvalidation_1-auc:0.78395\n",
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      "[194]\tvalidation_0-auc:0.99793\tvalidation_1-auc:0.78878\n",
      "[195]\tvalidation_0-auc:0.99785\tvalidation_1-auc:0.79036\n",
      "[196]\tvalidation_0-auc:0.99800\tvalidation_1-auc:0.79004\n",
      "[197]\tvalidation_0-auc:0.99801\tvalidation_1-auc:0.78999\n",
      "[198]\tvalidation_0-auc:0.99801\tvalidation_1-auc:0.78967\n",
      "[199]\tvalidation_0-auc:0.99802\tvalidation_1-auc:0.78983\n",
      "[200]\tvalidation_0-auc:0.99804\tvalidation_1-auc:0.78936\n",
      "[201]\tvalidation_0-auc:0.99820\tvalidation_1-auc:0.79025\n",
      "[202]\tvalidation_0-auc:0.99827\tvalidation_1-auc:0.78999\n",
      "[203]\tvalidation_0-auc:0.99842\tvalidation_1-auc:0.78983\n",
      "[204]\tvalidation_0-auc:0.99846\tvalidation_1-auc:0.78988\n",
      "[205]\tvalidation_0-auc:0.99845\tvalidation_1-auc:0.78983\n",
      "[206]\tvalidation_0-auc:0.99850\tvalidation_1-auc:0.79052\n",
      "[207]\tvalidation_0-auc:0.99861\tvalidation_1-auc:0.78983\n",
      "[208]\tvalidation_0-auc:0.99869\tvalidation_1-auc:0.78925\n",
      "[209]\tvalidation_0-auc:0.99870\tvalidation_1-auc:0.78798\n",
      "[210]\tvalidation_0-auc:0.99870\tvalidation_1-auc:0.78724\n",
      "[211]\tvalidation_0-auc:0.99877\tvalidation_1-auc:0.78777\n",
      "[212]\tvalidation_0-auc:0.99885\tvalidation_1-auc:0.78751\n",
      "[213]\tvalidation_0-auc:0.99884\tvalidation_1-auc:0.78598\n",
      "[214]\tvalidation_0-auc:0.99890\tvalidation_1-auc:0.78598\n",
      "[215]\tvalidation_0-auc:0.99892\tvalidation_1-auc:0.78561\n",
      "[216]\tvalidation_0-auc:0.99899\tvalidation_1-auc:0.78513\n",
      "[217]\tvalidation_0-auc:0.99899\tvalidation_1-auc:0.78513\n",
      "[218]\tvalidation_0-auc:0.99902\tvalidation_1-auc:0.78445\n",
      "[219]\tvalidation_0-auc:0.99908\tvalidation_1-auc:0.78482\n",
      "[220]\tvalidation_0-auc:0.99911\tvalidation_1-auc:0.78598\n",
      "[221]\tvalidation_0-auc:0.99916\tvalidation_1-auc:0.78461\n",
      "[222]\tvalidation_0-auc:0.99919\tvalidation_1-auc:0.78640\n",
      "[223]\tvalidation_0-auc:0.99917\tvalidation_1-auc:0.78624\n",
      "[224]\tvalidation_0-auc:0.99919\tvalidation_1-auc:0.78619\n",
      "[225]\tvalidation_0-auc:0.99919\tvalidation_1-auc:0.78503\n",
      "[226]\tvalidation_0-auc:0.99919\tvalidation_1-auc:0.78429\n",
      "[227]\tvalidation_0-auc:0.99925\tvalidation_1-auc:0.78476\n",
      "[228]\tvalidation_0-auc:0.99928\tvalidation_1-auc:0.78503\n",
      "[229]\tvalidation_0-auc:0.99929\tvalidation_1-auc:0.78445\n",
      "[230]\tvalidation_0-auc:0.99930\tvalidation_1-auc:0.78497\n",
      "[231]\tvalidation_0-auc:0.99938\tvalidation_1-auc:0.78429\n",
      "[232]\tvalidation_0-auc:0.99939\tvalidation_1-auc:0.78360\n",
      "[233]\tvalidation_0-auc:0.99936\tvalidation_1-auc:0.78424\n",
      "[234]\tvalidation_0-auc:0.99942\tvalidation_1-auc:0.78492\n",
      "[235]\tvalidation_0-auc:0.99943\tvalidation_1-auc:0.78455\n",
      "[236]\tvalidation_0-auc:0.99950\tvalidation_1-auc:0.78365\n",
      "[237]\tvalidation_0-auc:0.99951\tvalidation_1-auc:0.78365\n",
      "[238]\tvalidation_0-auc:0.99947\tvalidation_1-auc:0.78297\n",
      "[239]\tvalidation_0-auc:0.99954\tvalidation_1-auc:0.78286\n",
      "[240]\tvalidation_0-auc:0.99957\tvalidation_1-auc:0.78461\n",
      "[241]\tvalidation_0-auc:0.99958\tvalidation_1-auc:0.78313\n",
      "[242]\tvalidation_0-auc:0.99964\tvalidation_1-auc:0.78355\n",
      "[243]\tvalidation_0-auc:0.99964\tvalidation_1-auc:0.78439\n",
      "[244]\tvalidation_0-auc:0.99968\tvalidation_1-auc:0.78408\n",
      "[245]\tvalidation_0-auc:0.99967\tvalidation_1-auc:0.78450\n",
      "[246]\tvalidation_0-auc:0.99971\tvalidation_1-auc:0.78334\n",
      "[247]\tvalidation_0-auc:0.99972\tvalidation_1-auc:0.78355\n",
      "[248]\tvalidation_0-auc:0.99973\tvalidation_1-auc:0.78323\n",
      "[249]\tvalidation_0-auc:0.99972\tvalidation_1-auc:0.78408\n",
      "[250]\tvalidation_0-auc:0.99974\tvalidation_1-auc:0.78307\n",
      "[251]\tvalidation_0-auc:0.99974\tvalidation_1-auc:0.78239\n",
      "[252]\tvalidation_0-auc:0.99977\tvalidation_1-auc:0.78334\n",
      "[253]\tvalidation_0-auc:0.99978\tvalidation_1-auc:0.78339\n",
      "[254]\tvalidation_0-auc:0.99978\tvalidation_1-auc:0.78260\n",
      "[255]\tvalidation_0-auc:0.99978\tvalidation_1-auc:0.78323\n",
      "[256]\tvalidation_0-auc:0.99979\tvalidation_1-auc:0.78270\n",
      "[257]\tvalidation_0-auc:0.99979\tvalidation_1-auc:0.78292\n",
      "[258]\tvalidation_0-auc:0.99981\tvalidation_1-auc:0.78218\n",
      "[259]\tvalidation_0-auc:0.99984\tvalidation_1-auc:0.78107\n",
      "[260]\tvalidation_0-auc:0.99985\tvalidation_1-auc:0.78197\n",
      "[261]\tvalidation_0-auc:0.99987\tvalidation_1-auc:0.78138\n",
      "[262]\tvalidation_0-auc:0.99987\tvalidation_1-auc:0.78043\n",
      "[263]\tvalidation_0-auc:0.99987\tvalidation_1-auc:0.78033\n",
      "[264]\tvalidation_0-auc:0.99989\tvalidation_1-auc:0.78086\n",
      "[265]\tvalidation_0-auc:0.99991\tvalidation_1-auc:0.78133\n",
      "[266]\tvalidation_0-auc:0.99991\tvalidation_1-auc:0.78075\n",
      "[267]\tvalidation_0-auc:0.99992\tvalidation_1-auc:0.78165\n",
      "[268]\tvalidation_0-auc:0.99993\tvalidation_1-auc:0.78175\n",
      "[269]\tvalidation_0-auc:0.99993\tvalidation_1-auc:0.78212\n",
      "[270]\tvalidation_0-auc:0.99994\tvalidation_1-auc:0.78244\n",
      "[271]\tvalidation_0-auc:0.99992\tvalidation_1-auc:0.78170\n",
      "[272]\tvalidation_0-auc:0.99994\tvalidation_1-auc:0.78212\n",
      "[273]\tvalidation_0-auc:0.99994\tvalidation_1-auc:0.78249\n",
      "[274]\tvalidation_0-auc:0.99994\tvalidation_1-auc:0.78270\n",
      "[275]\tvalidation_0-auc:0.99994\tvalidation_1-auc:0.78160\n",
      "[276]\tvalidation_0-auc:0.99994\tvalidation_1-auc:0.78165\n",
      "[277]\tvalidation_0-auc:0.99995\tvalidation_1-auc:0.78244\n",
      "[278]\tvalidation_0-auc:0.99995\tvalidation_1-auc:0.78191\n",
      "[279]\tvalidation_0-auc:0.99995\tvalidation_1-auc:0.78133\n",
      "[280]\tvalidation_0-auc:0.99996\tvalidation_1-auc:0.78133\n",
      "[281]\tvalidation_0-auc:0.99995\tvalidation_1-auc:0.78138\n",
      "[282]\tvalidation_0-auc:0.99995\tvalidation_1-auc:0.78218\n",
      "[283]\tvalidation_0-auc:0.99995\tvalidation_1-auc:0.78202\n",
      "[284]\tvalidation_0-auc:0.99995\tvalidation_1-auc:0.78170\n",
      "[285]\tvalidation_0-auc:0.99996\tvalidation_1-auc:0.78080\n",
      "[286]\tvalidation_0-auc:0.99996\tvalidation_1-auc:0.78043\n",
      "[287]\tvalidation_0-auc:0.99996\tvalidation_1-auc:0.78096\n",
      "[288]\tvalidation_0-auc:0.99996\tvalidation_1-auc:0.78038\n",
      "[289]\tvalidation_0-auc:0.99996\tvalidation_1-auc:0.78043\n",
      "[290]\tvalidation_0-auc:0.99996\tvalidation_1-auc:0.78022\n",
      "[291]\tvalidation_0-auc:0.99998\tvalidation_1-auc:0.77964\n",
      "[292]\tvalidation_0-auc:0.99998\tvalidation_1-auc:0.77927\n",
      "[293]\tvalidation_0-auc:0.99998\tvalidation_1-auc:0.78033\n",
      "[294]\tvalidation_0-auc:0.99998\tvalidation_1-auc:0.77975\n",
      "[295]\tvalidation_0-auc:0.99998\tvalidation_1-auc:0.78001\n",
      "Stopping. Best iteration:\n",
      "[64]\tvalidation_0-auc:0.96566\tvalidation_1-auc:0.79976\n",
      "\n"
     ]
    }
   ],
   "source": [
    "train_x, test_x, train_y, test_y = train_test_split(data1, label1, test_size=0.3, random_state=42)\n",
    "model.fit(train_x,train_y,eval_metric='auc',eval_set=[(train_x, train_y),(test_x, test_y)],early_stopping_rounds=231)\n",
    "test_pre = model.predict_proba(testx)[:,1]#, num_iteration=model.best_iteration"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 16,
   "metadata": {
    "collapsed": true,
    "jupyter": {
     "outputs_hidden": true
    }
   },
   "outputs": [
    {
     "data": {
      "text/plain": [
       "array([0.05156057, 0.05159634, 0.09170836, 0.08669118, 0.71679911,\n",
       "       0.18779496, 0.48357816, 0.03157045, 0.02570339, 0.16633937,\n",
       "       0.03202088, 0.25811205, 0.04265133, 0.64964572, 0.06586367,\n",
       "       0.01315453, 0.04480904, 0.05769646, 0.03664752, 0.15710439,\n",
       "       0.67159932, 0.06307201, 0.03107177, 0.02615956, 0.23378223,\n",
       "       0.18724824, 0.04051908, 0.02870892, 0.59518669, 0.02541439,\n",
       "       0.02014252, 0.04315917, 0.14081975, 0.08596478, 0.03352067,\n",
       "       0.02682463, 0.10305614, 0.07077047, 0.05720926, 0.05417808,\n",
       "       0.05674894, 0.0717973 , 0.06415014, 0.07194091, 0.05254308,\n",
       "       0.43171326, 0.1936467 , 0.03337491, 0.74021111, 0.31471886,\n",
       "       0.11293298, 0.23826505, 0.05770435, 0.08941195, 0.41187277,\n",
       "       0.05739856, 0.03158168, 0.06496   , 0.01914905, 0.27027063,\n",
       "       0.02779915, 0.10094305, 0.02802784, 0.07468961, 0.26241613,\n",
       "       0.05879041, 0.09617592, 0.03798047, 0.06763417, 0.05963827,\n",
       "       0.06539715, 0.15970149, 0.05481354, 0.03239109, 0.02951846,\n",
       "       0.06643454, 0.05691249, 0.05872932, 0.16937795, 0.03078207,\n",
       "       0.01975247, 0.02783963, 0.01937815, 0.04402868, 0.05147201,\n",
       "       0.06150605, 0.03819436, 0.13549673, 0.06638025, 0.08678373,\n",
       "       0.64509935, 0.02543194, 0.06617833, 0.21523398, 0.02968233,\n",
       "       0.05384432, 0.10838742, 0.28500498, 0.0173566 , 0.05388585,\n",
       "       0.21792701, 0.16185687, 0.19430668, 0.05161051, 0.03360555,\n",
       "       0.0306086 , 0.09607563, 0.31575746, 0.11485073, 0.0486523 ,\n",
       "       0.21807662, 0.06873375, 0.03543308, 0.02477684, 0.13413531,\n",
       "       0.0440429 , 0.02202251, 0.09120774, 0.03018715, 0.01744096,\n",
       "       0.07607714, 0.01433988, 0.0295529 , 0.61009738, 0.21780697,\n",
       "       0.04226861, 0.01977272, 0.10931492, 0.09084908, 0.02848921,\n",
       "       0.02910697, 0.46655356, 0.35890243, 0.30268085, 0.08335706,\n",
       "       0.10796283, 0.28421705, 0.0805087 , 0.10069927, 0.0612025 ,\n",
       "       0.09125391, 0.03921051, 0.11096087, 0.08676483, 0.08852638,\n",
       "       0.05833447, 0.04897249, 0.04561373, 0.06874883, 0.05269177,\n",
       "       0.0523812 , 0.11198439, 0.05175045, 0.14360244, 0.0716447 ,\n",
       "       0.03016266, 0.05269694, 0.10220159, 0.05552657, 0.02561462,\n",
       "       0.42319665, 0.02864466, 0.23636401, 0.72261386, 0.02852067,\n",
       "       0.23035797, 0.28648504, 0.02451905, 0.0197808 , 0.03157878,\n",
       "       0.0369147 , 0.06763267, 0.03879708, 0.11854357, 0.02266621,\n",
       "       0.11185895, 0.05835971, 0.11644824, 0.14411618, 0.10964627,\n",
       "       0.01983112, 0.04629546, 0.0158233 , 0.59306187, 0.03802257,\n",
       "       0.01508795, 0.31373136, 0.03880443, 0.21015945, 0.11402898,\n",
       "       0.38677971, 0.46023239, 0.05663798, 0.01876543, 0.05747266,\n",
       "       0.06682112, 0.02576882, 0.02396615, 0.30078811, 0.04455392,\n",
       "       0.14084587, 0.04120346, 0.16548593, 0.03446965, 0.06144107,\n",
       "       0.06368678, 0.1777068 , 0.02951405, 0.04583205, 0.03941262,\n",
       "       0.09844872, 0.02872511, 0.02465782, 0.02850039, 0.03838904,\n",
       "       0.036481  , 0.04072878, 0.16282085, 0.06330385, 0.36494462,\n",
       "       0.10212379, 0.1881418 , 0.43270119, 0.11864567, 0.16913155,\n",
       "       0.03448496, 0.07603498, 0.52361124, 0.65727766, 0.13561613,\n",
       "       0.02330945, 0.38105959, 0.02883058, 0.04693749, 0.02230135,\n",
       "       0.18925488, 0.20369869, 0.01806538, 0.04497885, 0.02245069,\n",
       "       0.0833029 , 0.08234259, 0.03758735, 0.06643808, 0.0541152 ,\n",
       "       0.03399072, 0.05829774, 0.30702913, 0.03851448, 0.07043445,\n",
       "       0.08905728, 0.11952814, 0.15465193, 0.05514957, 0.14964823,\n",
       "       0.07878626, 0.03425677, 0.72030137, 0.09984351, 0.39638087,\n",
       "       0.10096913, 0.06185589, 0.12793264, 0.047995  , 0.04799105,\n",
       "       0.36096737, 0.01848177, 0.08912966, 0.10247944, 0.01668175,\n",
       "       0.05093176, 0.0207197 , 0.02741629, 0.08304175, 0.01449921,\n",
       "       0.02563234, 0.06360238, 0.16988135, 0.1258261 , 0.08042642,\n",
       "       0.14841812, 0.10407522, 0.05574162, 0.05067821, 0.10826877,\n",
       "       0.15368967, 0.01290068, 0.09838966, 0.07411374, 0.03672781,\n",
       "       0.0322775 , 0.23455129, 0.02215167, 0.06843551])"
      ]
     },
     "execution_count": 16,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "test_pre"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 20,
   "metadata": {},
   "outputs": [],
   "source": [
    "res=data[data['Attrition']==-1][['user_id']]\n",
    "res['Attrition'] = test_pre"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 21,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/html": [
       "<div>\n",
       "<style scoped>\n",
       "    .dataframe tbody tr th:only-of-type {\n",
       "        vertical-align: middle;\n",
       "    }\n",
       "\n",
       "    .dataframe tbody tr th {\n",
       "        vertical-align: top;\n",
       "    }\n",
       "\n",
       "    .dataframe thead th {\n",
       "        text-align: right;\n",
       "    }\n",
       "</style>\n",
       "<table border=\"1\" class=\"dataframe\">\n",
       "  <thead>\n",
       "    <tr style=\"text-align: right;\">\n",
       "      <th></th>\n",
       "      <th>user_id</th>\n",
       "      <th>Attrition</th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th>1176</th>\n",
       "      <td>442</td>\n",
       "      <td>0.098802</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>1177</th>\n",
       "      <td>1091</td>\n",
       "      <td>0.075760</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>1178</th>\n",
       "      <td>981</td>\n",
       "      <td>0.091652</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>1179</th>\n",
       "      <td>785</td>\n",
       "      <td>0.114376</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>1180</th>\n",
       "      <td>1332</td>\n",
       "      <td>0.843049</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>...</th>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>1465</th>\n",
       "      <td>1439</td>\n",
       "      <td>0.048095</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>1466</th>\n",
       "      <td>481</td>\n",
       "      <td>0.068604</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>1467</th>\n",
       "      <td>124</td>\n",
       "      <td>0.182645</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>1468</th>\n",
       "      <td>198</td>\n",
       "      <td>0.039690</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>1469</th>\n",
       "      <td>1229</td>\n",
       "      <td>0.088963</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "<p>294 rows × 2 columns</p>\n",
       "</div>"
      ],
      "text/plain": [
       "      user_id  Attrition\n",
       "1176      442   0.098802\n",
       "1177     1091   0.075760\n",
       "1178      981   0.091652\n",
       "1179      785   0.114376\n",
       "1180     1332   0.843049\n",
       "...       ...        ...\n",
       "1465     1439   0.048095\n",
       "1466      481   0.068604\n",
       "1467      124   0.182645\n",
       "1468      198   0.039690\n",
       "1469     1229   0.088963\n",
       "\n",
       "[294 rows x 2 columns]"
      ]
     },
     "execution_count": 21,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "res"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 27,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "16"
      ]
     },
     "execution_count": 27,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "len(res[res['Attrition']>0.5])"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 86,
   "metadata": {},
   "outputs": [],
   "source": [
    "# res.loc[res['pred']!='Yes','pred']='No'"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 20,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "0.050885    1\n",
       "0.526917    1\n",
       "0.063105    1\n",
       "0.064363    1\n",
       "0.050913    1\n",
       "           ..\n",
       "0.086145    1\n",
       "0.220473    1\n",
       "0.202025    1\n",
       "0.596310    1\n",
       "0.050653    1\n",
       "Name: Attrition, Length: 294, dtype: int64"
      ]
     },
     "execution_count": 20,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "res.Attrition.value_counts()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 21,
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "<class 'pandas.core.frame.DataFrame'>\n",
      "Int64Index: 294 entries, 1176 to 1469\n",
      "Data columns (total 2 columns):\n",
      " #   Column     Non-Null Count  Dtype  \n",
      "---  ------     --------------  -----  \n",
      " 0   user_id    294 non-null    int64  \n",
      " 1   Attrition  294 non-null    float64\n",
      "dtypes: float64(1), int64(1)\n",
      "memory usage: 6.9 KB\n"
     ]
    }
   ],
   "source": [
    "res.info()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 27,
   "metadata": {},
   "outputs": [
    {
     "data": {
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       "      user_id  Attrition\n",
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       "1180     1332   0.716799\n",
       "...       ...        ...\n",
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       "[294 rows x 2 columns]"
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     "execution_count": 27,
     "metadata": {},
     "output_type": "execute_result"
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    "res[['user_id','Attrition']]"
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  },
  {
   "cell_type": "code",
   "execution_count": 23,
   "metadata": {},
   "outputs": [],
   "source": [
    "res.to_csv(path + 'output/xgb_drop_baseline.csv',index=False )"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 14,
   "metadata": {
    "collapsed": true,
    "jupyter": {
     "outputs_hidden": true
    }
   },
   "outputs": [
    {
     "name": "stdout",
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      "[09:04:15] WARNING: C:\\Users\\Administrator\\workspace\\xgboost-win64_release_1.1.0\\src\\learner.cc:480: \n",
      "Parameters: { colsample_btree } might not be used.\n",
      "\n",
      "  This may not be accurate due to some parameters are only used in language bindings but\n",
      "  passed down to XGBoost core.  Or some parameters are not used but slip through this\n",
      "  verification. Please open an issue if you find above cases.\n",
      "\n",
      "\n",
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      "******************************************************\n",
      "[09:04:16] WARNING: C:\\Users\\Administrator\\workspace\\xgboost-win64_release_1.1.0\\src\\learner.cc:480: \n",
      "Parameters: { colsample_btree } might not be used.\n",
      "\n",
      "  This may not be accurate due to some parameters are only used in language bindings but\n",
      "  passed down to XGBoost core.  Or some parameters are not used but slip through this\n",
      "  verification. Please open an issue if you find above cases.\n",
      "\n",
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      "******************************************************\n",
      "[09:04:18] WARNING: C:\\Users\\Administrator\\workspace\\xgboost-win64_release_1.1.0\\src\\learner.cc:480: \n",
      "Parameters: { colsample_btree } might not be used.\n",
      "\n",
      "  This may not be accurate due to some parameters are only used in language bindings but\n",
      "  passed down to XGBoost core.  Or some parameters are not used but slip through this\n",
      "  verification. Please open an issue if you find above cases.\n",
      "\n",
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      "******************************************************\n",
      "[09:04:19] WARNING: C:\\Users\\Administrator\\workspace\\xgboost-win64_release_1.1.0\\src\\learner.cc:480: \n",
      "Parameters: { colsample_btree } might not be used.\n",
      "\n",
      "  This may not be accurate due to some parameters are only used in language bindings but\n",
      "  passed down to XGBoost core.  Or some parameters are not used but slip through this\n",
      "  verification. Please open an issue if you find above cases.\n",
      "\n",
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      "[299]\tvalidation_0-auc:0.99993\tvalidation_1-auc:0.76769\n",
      "******************************************************\n",
      "[09:04:21] WARNING: C:\\Users\\Administrator\\workspace\\xgboost-win64_release_1.1.0\\src\\learner.cc:480: \n",
      "Parameters: { colsample_btree } might not be used.\n",
      "\n",
      "  This may not be accurate due to some parameters are only used in language bindings but\n",
      "  passed down to XGBoost core.  Or some parameters are not used but slip through this\n",
      "  verification. Please open an issue if you find above cases.\n",
      "\n",
      "\n",
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      "[229]\tvalidation_0-auc:0.99950\tvalidation_1-auc:0.80496\n",
      "[230]\tvalidation_0-auc:0.99951\tvalidation_1-auc:0.80388\n",
      "[231]\tvalidation_0-auc:0.99951\tvalidation_1-auc:0.80373\n",
      "[232]\tvalidation_0-auc:0.99950\tvalidation_1-auc:0.80280\n",
      "[233]\tvalidation_0-auc:0.99950\tvalidation_1-auc:0.80311\n",
      "[234]\tvalidation_0-auc:0.99952\tvalidation_1-auc:0.80296\n",
      "[235]\tvalidation_0-auc:0.99957\tvalidation_1-auc:0.80357\n",
      "[236]\tvalidation_0-auc:0.99960\tvalidation_1-auc:0.80342\n",
      "[237]\tvalidation_0-auc:0.99957\tvalidation_1-auc:0.80403\n",
      "[238]\tvalidation_0-auc:0.99961\tvalidation_1-auc:0.80419\n",
      "[239]\tvalidation_0-auc:0.99961\tvalidation_1-auc:0.80511\n",
      "[240]\tvalidation_0-auc:0.99961\tvalidation_1-auc:0.80573\n",
      "[241]\tvalidation_0-auc:0.99964\tvalidation_1-auc:0.80449\n",
      "[242]\tvalidation_0-auc:0.99965\tvalidation_1-auc:0.80480\n",
      "[243]\tvalidation_0-auc:0.99965\tvalidation_1-auc:0.80496\n",
      "[244]\tvalidation_0-auc:0.99966\tvalidation_1-auc:0.80449\n",
      "[245]\tvalidation_0-auc:0.99967\tvalidation_1-auc:0.80403\n",
      "[246]\tvalidation_0-auc:0.99968\tvalidation_1-auc:0.80326\n",
      "[247]\tvalidation_0-auc:0.99970\tvalidation_1-auc:0.80342\n",
      "[248]\tvalidation_0-auc:0.99968\tvalidation_1-auc:0.80465\n",
      "[249]\tvalidation_0-auc:0.99975\tvalidation_1-auc:0.80465\n",
      "[250]\tvalidation_0-auc:0.99972\tvalidation_1-auc:0.80296\n",
      "[251]\tvalidation_0-auc:0.99975\tvalidation_1-auc:0.80326\n",
      "[252]\tvalidation_0-auc:0.99975\tvalidation_1-auc:0.80326\n",
      "[253]\tvalidation_0-auc:0.99972\tvalidation_1-auc:0.80542\n",
      "[254]\tvalidation_0-auc:0.99974\tvalidation_1-auc:0.80527\n",
      "[255]\tvalidation_0-auc:0.99977\tvalidation_1-auc:0.80434\n",
      "[256]\tvalidation_0-auc:0.99977\tvalidation_1-auc:0.80449\n",
      "[257]\tvalidation_0-auc:0.99978\tvalidation_1-auc:0.80388\n",
      "[258]\tvalidation_0-auc:0.99979\tvalidation_1-auc:0.80388\n",
      "[259]\tvalidation_0-auc:0.99975\tvalidation_1-auc:0.80419\n",
      "[260]\tvalidation_0-auc:0.99980\tvalidation_1-auc:0.80326\n",
      "[261]\tvalidation_0-auc:0.99983\tvalidation_1-auc:0.80049\n",
      "[262]\tvalidation_0-auc:0.99983\tvalidation_1-auc:0.80126\n",
      "[263]\tvalidation_0-auc:0.99983\tvalidation_1-auc:0.80065\n",
      "[264]\tvalidation_0-auc:0.99982\tvalidation_1-auc:0.80265\n",
      "[265]\tvalidation_0-auc:0.99983\tvalidation_1-auc:0.80373\n",
      "[266]\tvalidation_0-auc:0.99984\tvalidation_1-auc:0.80465\n",
      "[267]\tvalidation_0-auc:0.99983\tvalidation_1-auc:0.80188\n",
      "[268]\tvalidation_0-auc:0.99983\tvalidation_1-auc:0.80265\n",
      "[269]\tvalidation_0-auc:0.99985\tvalidation_1-auc:0.80342\n",
      "[270]\tvalidation_0-auc:0.99988\tvalidation_1-auc:0.80249\n",
      "[271]\tvalidation_0-auc:0.99990\tvalidation_1-auc:0.80234\n",
      "[272]\tvalidation_0-auc:0.99991\tvalidation_1-auc:0.80203\n",
      "[273]\tvalidation_0-auc:0.99989\tvalidation_1-auc:0.80296\n",
      "[274]\tvalidation_0-auc:0.99989\tvalidation_1-auc:0.80326\n",
      "[275]\tvalidation_0-auc:0.99991\tvalidation_1-auc:0.80111\n",
      "[276]\tvalidation_0-auc:0.99990\tvalidation_1-auc:0.80234\n",
      "[277]\tvalidation_0-auc:0.99990\tvalidation_1-auc:0.80065\n",
      "[278]\tvalidation_0-auc:0.99990\tvalidation_1-auc:0.79941\n",
      "[279]\tvalidation_0-auc:0.99991\tvalidation_1-auc:0.79803\n",
      "[280]\tvalidation_0-auc:0.99992\tvalidation_1-auc:0.79741\n",
      "[281]\tvalidation_0-auc:0.99994\tvalidation_1-auc:0.79757\n",
      "[282]\tvalidation_0-auc:0.99994\tvalidation_1-auc:0.79695\n",
      "[283]\tvalidation_0-auc:0.99994\tvalidation_1-auc:0.79680\n",
      "[284]\tvalidation_0-auc:0.99995\tvalidation_1-auc:0.79788\n",
      "[285]\tvalidation_0-auc:0.99995\tvalidation_1-auc:0.79941\n",
      "[286]\tvalidation_0-auc:0.99995\tvalidation_1-auc:0.79849\n",
      "[287]\tvalidation_0-auc:0.99995\tvalidation_1-auc:0.79803\n",
      "[288]\tvalidation_0-auc:0.99996\tvalidation_1-auc:0.79803\n",
      "[289]\tvalidation_0-auc:0.99997\tvalidation_1-auc:0.80003\n",
      "[290]\tvalidation_0-auc:0.99997\tvalidation_1-auc:0.80142\n",
      "[291]\tvalidation_0-auc:0.99997\tvalidation_1-auc:0.80157\n",
      "[292]\tvalidation_0-auc:0.99998\tvalidation_1-auc:0.80019\n",
      "[293]\tvalidation_0-auc:0.99998\tvalidation_1-auc:0.80003\n",
      "[294]\tvalidation_0-auc:0.99998\tvalidation_1-auc:0.79957\n",
      "[295]\tvalidation_0-auc:0.99998\tvalidation_1-auc:0.79926\n",
      "[296]\tvalidation_0-auc:0.99998\tvalidation_1-auc:0.79911\n",
      "[297]\tvalidation_0-auc:0.99998\tvalidation_1-auc:0.79926\n",
      "[298]\tvalidation_0-auc:0.99998\tvalidation_1-auc:0.79880\n",
      "[299]\tvalidation_0-auc:0.99998\tvalidation_1-auc:0.79788\n",
      "******************************************************\n"
     ]
    }
   ],
   "source": [
    "#5折交叉验证\n",
    "from sklearn.model_selection import KFold,StratifiedKFold\n",
    "n_splits=5\n",
    "kfold = KFold(n_splits=n_splits, shuffle=True, random_state=42)\n",
    "\n",
    "\n",
    "train_x = data[data['Attrition']!=-1][feats]\n",
    "train_y = data[data['Attrition']!=-1]['Attrition']\n",
    "\n",
    "\n",
    "res=data[data['Attrition']==-1][['user_id']]\n",
    "res['Attrition'] = 0\n",
    "\n",
    "\n",
    "test_x= data[data['Attrition']==-1][feats]\n",
    "\n",
    "for train_idx, val_idx in kfold.split(train_x):\n",
    "    model.random_state = model.random_state + 1\n",
    "    train_x1 = train_x.loc[train_idx]\n",
    "    train_y1 = train_y.loc[train_idx]\n",
    "    test_x1 = train_x.loc[val_idx]\n",
    "    test_y1 = train_y.loc[val_idx]\n",
    "    #,(vali_x,vali_y)\n",
    "    model.fit(train_x1, train_y1,eval_set=[(train_x1, train_y1),(test_x1, test_y1)],eval_metric='auc')\n",
    "    print('******************************************************')\n",
    "    res['Attrition'] += model.predict_proba(test_x)[:,1]\n",
    "    \n",
    "\n"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 15,
   "metadata": {},
   "outputs": [
    {
     "data": {
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       "  <thead>\n",
       "    <tr style=\"text-align: right;\">\n",
       "      <th></th>\n",
       "      <th>user_id</th>\n",
       "      <th>Attrition</th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th>1179</th>\n",
       "      <td>785</td>\n",
       "      <td>0.565794</td>\n",
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       "    <tr>\n",
       "      <th>1180</th>\n",
       "      <td>1332</td>\n",
       "      <td>4.595156</td>\n",
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       "      <td>1.123582</td>\n",
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       "      <td>1058</td>\n",
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       "    <tr>\n",
       "      <th>1185</th>\n",
       "      <td>122</td>\n",
       "      <td>0.535860</td>\n",
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       "      <th>1455</th>\n",
       "      <td>505</td>\n",
       "      <td>0.741211</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>1456</th>\n",
       "      <td>443</td>\n",
       "      <td>2.012967</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>1458</th>\n",
       "      <td>516</td>\n",
       "      <td>0.713707</td>\n",
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       "    <tr>\n",
       "      <th>1463</th>\n",
       "      <td>985</td>\n",
       "      <td>0.833326</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>1467</th>\n",
       "      <td>124</td>\n",
       "      <td>2.205549</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "<p>98 rows × 2 columns</p>\n",
       "</div>"
      ],
      "text/plain": [
       "      user_id  Attrition\n",
       "1179      785   0.565794\n",
       "1180     1332   4.595156\n",
       "1181      501   1.123582\n",
       "1182     1058   1.499860\n",
       "1185      122   0.535860\n",
       "...       ...        ...\n",
       "1455      505   0.741211\n",
       "1456      443   2.012967\n",
       "1458      516   0.713707\n",
       "1463      985   0.833326\n",
       "1467      124   2.205549\n",
       "\n",
       "[98 rows x 2 columns]"
      ]
     },
     "execution_count": 15,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "res[res['Attrition']>0.5]"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 16,
   "metadata": {},
   "outputs": [],
   "source": [
    "res['Attrition'] = res['Attrition']/n_splits"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 17,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "18"
      ]
     },
     "execution_count": 17,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "len(res[res['Attrition']>0.5])"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 18,
   "metadata": {},
   "outputs": [],
   "source": [
    "res.to_csv('./output/xgb_maxminscalar_notdrop_5fold.csv', index=False)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 23,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "(25317,)"
      ]
     },
     "execution_count": 23,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "train_y.shape"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "metadata": {},
   "outputs": [],
   "source": []
  }
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